Run the MNE BIDS Pipeline¶

Instead of the manual implementation using MNE, for this project the MNE-BIDS-Pipeline is chosen. The advantages of the pipeline include the clear sequential structure, the reproducability, and caching, as the authors write on MNE-BIDS-Pipeline overview.

On the one hand, the structure introduces additional effort in some steps like customisations, on the other hand, it can help new users of EEG signal processing with their first steps. Additionally, the reproducability helps in the collaboration over different operating systems. And in the development, the caching helps to reduce the delay between subsequent changes due to tests running the pipeline.

These reasons led to the use of MNE-BIDS-Pipeline. Therefore, this kind of implementation is given below in this notebook.

Steps for Running this Notebook¶

  1. Clone the Git repository of this project. (Since the Notebook is available, this step should be fulfilled.)
  2. Set the number of parallel jobs to a value matching RAM (≤ 1 GB per job) and CPU core number (≤ 1 job per core) of the used system.
    • More jobs allow for shorter total execution time. In test ran - depending on n_jobs - for about 30 to 60 minutes.
    • The parameter is n_jobs in ./mne-bids/config/mne-bids-pipeline.py which in the current version is set in line 2125.
  3. Run preparatory notebook prepare_data.ipynb to install dependencies, download, and patch the dataset.
  4. Run the pipeline with checkups by running this notebook.

Header: Load Modules, Set and Load Parameters, Define Functions¶

Prior to running the main steps of the pipeline, multiple steps need to be performed:

  • Load modules: Load modules needed for all (e. g. MNE BIDS pipeline), or few (e. g. typing) pipeline steps. Load custom modules (e. g. ica_helpers)
  • Set and load parameters: Set the relative (or absolute) path to the pipeline configuration, and load the configuration from the file.
In [1]:
# import basic EEG manipulation and analysis modules
import mne_bids_pipeline
import pandas
import pandas as pd

# import function to load configuration from file
from mne_bids_pipeline._config_import import _import_config as getConfig

# allow for accessing the command line within Python
import sys
In [55]:
# allow for checkup plots based on data stored in files
import mne # module for e.g. loading raw, or epoched signals from file
import matplotlib
import matplotlib.pyplot as plt # plotting module
%matplotlib inline
In [3]:
# set the file path of the main configuration file
config_path = "./mne-bids/config/mne-bids-pipeline.py"
In [4]:
# define a function which gets used in application of the ICA results to the raw data
import src.tools.ica_helpers as ih
In [5]:
# custom module for plotting
import src.tools.plot_power as pp
import src.tools.cmd as cmd
In [6]:
# Custom command line output
import src.tools.logtools as log

In order to speed up testing, we can enable and disable each individual pipeline step. STEPS_TO_RUN overrides this mechanic, forcing a full run of the pipeline.

In [7]:
# set steps to be run in this running iteration
# This helps to reduce the duration of runs in the project development.
STEPS_TO_RUN = {
    "init": False,
    "preprocessing/_01_data_quality": False,
    "preprocessing/_02_head_pos": False,
    "preprocessing/_03_maxfilter": False,
    "preprocessing/_04_frequency_filter": False,
    "preprocessing/_05_make_epochs": False,
    "preprocessing/_06a_run_ica": False,
    "preprocessing_apply_icalabel": False,
    "preprocessing/_07a_apply_ica": False,
    "preprocessing/_08_ptp_reject": False,
    "sensor": False,
    "source": False,
}

RUN_ALL_STEPS = True
In [8]:
if RUN_ALL_STEPS:
    for step in STEPS_TO_RUN:
        STEPS_TO_RUN[step] = True

Pipeline¶

Start the pipeline running these steps:

  • preprocessing/_01_data_quality
  • preprocessing/_04_frequency_filter
  • preprocessing/_05_make_epochs
  • preprocessing/_06a_run_ica, ica labelling, preprocessing/_07a_apply_ica
  • preprocessing/_08_ptp_reject
  • sensor
  • source

Each of the steps contains one or more checkups for validating the results of the step.

Since the step names of MNE BIDS pipeline were changed after the start of this notebooks creation, the step names should get updated for use with another module version. The simplest version could be to run all pre-processing by running preprocessing instead of the minor steps preprocessing/_0*_*.

Initial Setup¶

First, the selected pipeline configuration gets loaded. Few of its entries get printed as checkup.

Then, the initial preparations for running the pipeline get started: configuration loading and directory creation. This also is followed by a checkup.

In [9]:
# load configured settings from file
cfg = getConfig(
    config_path=config_path
)
In [10]:
# checkup: print config contents
print(
    "study name:\t\t", cfg.study_name, 
    "\nsubjects dir:\t\t", cfg.subjects_dir, 
    "\ntask:\t\t\t", cfg.task, 
    "\nconditions:\t\t", cfg.conditions, 
    "\nraw resample sfreq:\t", cfg.raw_resample_sfreq,
    "\nl/h freq:\t\t", [cfg.l_freq, cfg.h_freq],
    "\nica max iterations:\t", cfg.ica_max_iterations, 
    "\nica n components:\t", cfg.ica_n_components, 
    "\ndecoding csp freqs:\t", cfg.decoding_csp_freqs
)

study name:		 EEG-course-project 
subjects dir:		 ./data/ds003702/ 
task:			 SocialMemoryCuing 
conditions:		 ['avatar', 'sticks'] 
raw resample sfreq:	 100.0 
l/h freq:		 [1.0, 30.0] 
ica max iterations:	 3000 
ica n components:	 0.95 
decoding csp freqs:	 {'theta': [3, 7], 'alpha': [8, 12]}
In [54]:
# checkup: # print end of path to the stored bids root path
print(f"…/{cfg.bids_root.parts[-2]}/{cfg.bids_root.parts[-1]}/")

…/data/ds003702/

In the next cell, the initialisation pipeline step gets run. Since the notebook 01_prepare_data.ipynb should already have been run, it should not need to do anything.

In [12]:
curr_steps = "init"
if curr_steps in STEPS_TO_RUN and STEPS_TO_RUN[curr_steps]:
    !mne_bids_pipeline --config {config_path} --steps {curr_steps}

┌────────┬ Welcome aboard MNE-BIDS-Pipeline! 👋 ────────────────────────────────
│22:38:41│ 📝 Using configuration: ./mne-bids/config/mne-bids-pipeline.py
└────────┴ 
┌────────┬ init/_01_init_derivatives_dir ───────────────────────────────────────
│22:38:41│ ✅ Output directories already exist …
└────────┴ done (1s)
┌────────┬ init/_02_find_empty_room ────────────────────────────────────────────
│22:38:41│ ⏩ Skipping, empty-room data only relevant for MEG …
└────────┴ done (1s)
┌────────┬ init/_01_init_derivatives_dir ───────────────────────────────────────
│22:38:41│ ✅ Output directories already exist …
└────────┴ done (1s)
┌────────┬ init/_02_find_empty_room ────────────────────────────────────────────
│22:38:41│ ⏩ Skipping, empty-room data only relevant for MEG …
└────────┴ done (1s)
In [13]:
# checkup: check, whether output directory was created
#          The derivatives directory should exist and contain a subfolder per selected subject.
#          The subjects subfolders should be empty if no data were alread generated.
curr_bids_root = cfg.bids_root.__str__()
cmd.ls(curr_bids_root + '/derivatives/mne-bids-pipeline/')

sub-13
sub-28
sub-18
sub-43
sub-33
sub-03
sub-04
sub-02
sub-34
sub-26
sub-12
sub-15
sub-41
sub-16
sub-40
sub-39
sub-30
sub-01
sub-21
sub-45
sub-25
sub-19
sub-44
sub-07
sub-14
sub-17
sub-38
sub-35
sub-11
sub-24
sub-48
sub-10
sub-32
sub-27
sub-49
sub-50
sub-06
sub-46
sub-09
sub-23
dataset_description.json
sub-22

Since several subject directories get displayed, the output directories seem to be created.

Pre-processing: Data Quality¶

Next, an investsigation on the provided data set is started. Per subject, a report gets created. A simple checkup is used to print an excerpt of one of the checkups.

In [14]:
curr_steps = "preprocessing/_01_data_quality"
if curr_steps in STEPS_TO_RUN and STEPS_TO_RUN[curr_steps]:
    !mne_bids_pipeline --config {config_path} --steps {curr_steps}

┌────────┬ Welcome aboard MNE-BIDS-Pipeline! 👋 ────────────────────────────────
│22:38:43│ 📝 Using configuration: ./mne-bids/config/mne-bids-pipeline.py
└────────┴ 
┌────────┬ init/_01_init_derivatives_dir ───────────────────────────────────────
│22:38:43│ ✅ Output directories already exist …
└────────┴ done (1s)
┌────────┬ init/_02_find_empty_room ────────────────────────────────────────────
│22:38:43│ ⏩ Skipping, empty-room data only relevant for MEG …
└────────┴ done (1s)
┌────────┬ preprocessing/_01_data_quality ──────────────────────────────────────
│22:38:44│ ⏳️ sub-01 Initializing report HDF5 file
│22:38:44│ ⏳️ sub-03 Initializing report HDF5 file
│22:38:44│ ⏳️ sub-04 Initializing report HDF5 file
│22:38:44│ ⏳️ sub-02 Initializing report HDF5 file
│22:38:44│ ⏳️ sub-03 Adding original raw data to report
│22:38:44│ ⏳️ sub-01 Adding original raw data to report
│22:38:44│ ⏳️ sub-04 Adding original raw data to report
│22:38:44│ ⏳️ sub-06 Initializing report HDF5 file
│22:38:44│ ⏳️ sub-02 Adding original raw data to report
│22:38:44│ ⏳️ sub-07 Initializing report HDF5 file
│22:38:44│ ⏳️ sub-06 Adding original raw data to report
│22:38:44│ ⏳️ sub-07 Adding original raw data to report
│22:38:55│ ⏳️ sub-07 Adding config and sys info to report
│22:38:55│ ⏳️ sub-06 Adding config and sys info to report
│22:38:56│ ⏳️ sub-02 Adding config and sys info to report
│22:38:56│ ⏳️ sub-04 Adding config and sys info to report
│22:38:57│ ⏳️ sub-01 Adding config and sys info to report
│22:38:57│ ⏳️ sub-03 Adding config and sys info to report
│22:38:58│ ⏳️ sub-07 Saving report: ]8;id=840003;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=279212;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=853649;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\(]8;;\]8;id=452610;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=853649;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\)]8;;\]8;id=840003;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/]8;;\]8;id=279212;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\sub-07_task-SocialMemoryCuing_report.html]8;;\
│22:38:58│ ⏳️ sub-06 Saving report: ]8;id=739298;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=688492;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=950332;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\(]8;;\]8;id=186883;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=950332;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\)]8;;\]8;id=739298;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/]8;;\]8;id=688492;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\sub-06_task-SocialMemoryCuing_report.html]8;;\
│22:38:58│ ⏳️ sub-09 Initializing report HDF5 file
│22:38:58│ ⏳️ sub-10 Initializing report HDF5 file
│22:38:58│ ⏳️ sub-09 Adding original raw data to report
│22:38:59│ ⏳️ sub-10 Adding original raw data to report
│22:38:59│ ⏳️ sub-02 Saving report: ]8;id=268472;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=301614;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=770756;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\(]8;;\]8;id=767373;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=770756;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\)]8;;\]8;id=268472;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/]8;;\]8;id=301614;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\sub-02_task-SocialMemoryCuing_report.html]8;;\
│22:38:59│ ⏳️ sub-04 Saving report: ]8;id=576946;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=125862;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=582438;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\(]8;;\]8;id=871845;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=582438;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\)]8;;\]8;id=576946;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/]8;;\]8;id=125862;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\sub-04_task-SocialMemoryCuing_report.html]8;;\
│22:38:59│ ⏳️ sub-11 Initializing report HDF5 file
│22:38:59│ ⏳️ sub-12 Initializing report HDF5 file
│22:38:59│ ⏳️ sub-11 Adding original raw data to report
│22:38:59│ ⏳️ sub-12 Adding original raw data to report
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│22:39:00│ ⏳️ sub-03 Saving report: ]8;id=663149;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=460948;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=99629;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\(]8;;\]8;id=237170;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=99629;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\)]8;;\]8;id=663149;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/]8;;\]8;id=460948;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\sub-03_task-SocialMemoryCuing_report.html]8;;\
│22:39:00│ ⏳️ sub-13 Initializing report HDF5 file
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│22:39:08│ ⏳️ sub-15 Initializing report HDF5 file
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│22:39:08│ ⏳️ sub-12 Adding config and sys info to report
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│22:39:08│ ⏳️ sub-16 Initializing report HDF5 file
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│22:39:09│ ⏳️ sub-10 Adding config and sys info to report
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│22:39:09│ ⏳️ sub-17 Initializing report HDF5 file
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│22:39:10│ ⏳️ sub-11 Adding config and sys info to report
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│22:39:10│ ⏳️ sub-18 Initializing report HDF5 file
│22:39:10│ ⏳️ sub-18 Adding original raw data to report
│22:39:10│ ⏳️ sub-14 Adding config and sys info to report
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│22:39:10│ ⏳️ sub-19 Initializing report HDF5 file
│22:39:10│ ⏳️ sub-19 Adding original raw data to report
│22:39:11│ ⏳️ sub-13 Adding config and sys info to report
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│22:39:11│ ⏳️ sub-21 Initializing report HDF5 file
│22:39:11│ ⏳️ sub-21 Adding original raw data to report
│22:39:17│ ⏳️ sub-15 Adding config and sys info to report
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│22:39:17│ ⏳️ sub-22 Initializing report HDF5 file
│22:39:17│ ⏳️ sub-22 Adding original raw data to report
│22:39:18│ ⏳️ sub-16 Adding config and sys info to report
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│22:39:18│ ⏳️ sub-23 Initializing report HDF5 file
│22:39:18│ ⏳️ sub-23 Adding original raw data to report
│22:39:20│ ⏳️ sub-17 Adding config and sys info to report
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│22:39:20│ ⏳️ sub-24 Initializing report HDF5 file
│22:39:20│ ⏳️ sub-24 Adding original raw data to report
│22:39:21│ ⏳️ sub-18 Adding config and sys info to report
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│22:39:21│ ⏳️ sub-25 Initializing report HDF5 file
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│22:39:21│ ⏳️ sub-26 Initializing report HDF5 file
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│22:39:21│ ⏳️ sub-21 Adding config and sys info to report
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│22:39:22│ ⏳️ sub-27 Initializing report HDF5 file
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│22:39:27│ ⏳️ sub-22 Adding config and sys info to report
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│22:39:27│ ⏳️ sub-28 Initializing report HDF5 file
│22:39:27│ ⏳️ sub-28 Adding original raw data to report
│22:39:27│ ⏳️ sub-23 Adding config and sys info to report
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│22:39:27│ ⏳️ sub-30 Initializing report HDF5 file
│22:39:27│ ⏳️ sub-30 Adding original raw data to report
│22:39:29│ ⏳️ sub-24 Adding config and sys info to report
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│22:39:29│ ⏳️ sub-32 Initializing report HDF5 file
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│22:39:30│ ⏳️ sub-25 Adding config and sys info to report
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│22:39:30│ ⏳️ sub-33 Initializing report HDF5 file
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│22:39:36│ ⏳️ sub-39 Initializing report HDF5 file
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│22:39:39│ ⏳️ sub-40 Initializing report HDF5 file
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│22:39:40│ ⏳️ sub-41 Initializing report HDF5 file
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│22:39:41│ ⏳️ sub-43 Initializing report HDF5 file
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│22:39:44│ ⏳️ sub-44 Initializing report HDF5 file
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│22:39:45│ ⏳️ sub-45 Initializing report HDF5 file
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│22:39:50│ ⏳️ sub-49 Initializing report HDF5 file
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│22:39:51│ ⏳️ sub-50 Initializing report HDF5 file
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│22:39:54│ ⏳️ sub-46 Adding config and sys info to report
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│22:39:55│ ⏳️ sub-45 Adding config and sys info to report
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│22:39:57│ ⏳️ sub-48 Adding config and sys info to report
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│22:39:57│ ⏳️ sub-49 Adding config and sys info to report
│22:39:57│ ⏳️ sub-49 Saving report: ]8;id=873807;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=780033;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=419690;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\(]8;;\]8;id=475938;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=419690;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\)]8;;\]8;id=873807;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/]8;;\]8;id=780033;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\sub-49_task-SocialMemoryCuing_report.html]8;;\
│22:39:58│ ⏳️ sub-50 Adding config and sys info to report
│22:39:58│ ⏳️ sub-50 Saving report: ]8;id=618107;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=629109;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=651298;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\(]8;;\]8;id=829960;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=651298;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\)]8;;\]8;id=618107;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/]8;;\]8;id=629109;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\sub-50_task-SocialMemoryCuing_report.html]8;;\
└────────┴ done (1m 16s)
In [15]:
# checkup: print some content which was written to file
import h5py

# set filename
curr_checkup_filename = f"{curr_bids_root}/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.h5"

# print file name if file exists
cmd.ls(curr_checkup_filename)


# import data
curr_checkup_h5file = h5py.File(curr_checkup_filename, 'r')
curr_html_length = len(curr_checkup_h5file["mnepython/key__content/idx_0/key_html"])
htmlContent = ''.join([ chr(curr_checkup_h5file["mnepython/key__content/idx_0/key_html"][idx] ) for idx in range(curr_html_length) ])
curr_checkup_h5file.close()
# print excerpt of html output
print(f"[...]\n{htmlContent[2500:2850]}\n[...]")

# print hint regarding extra data
print("\n===\nmore data: see at..")
# for more data, open the written html report file
cmd.ls("./" + cfg.bids_root.parts[-2] + "/" +cfg.bids_root.parts[-1] + "/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html")

sub-01_task-SocialMemoryCuing_report.h5
[...]
</details>
        <details open>
            <summary><strong>Data</strong></summary>
            <table class="table table-hover table-striped table-sm table-responsive small">
                
                <tr>
                    <th>Sampling frequency</th>
                    <td>500.00 Hz</td>
                </tr>
                
       
[...]

===
more data: see at..
sub-01_task-SocialMemoryCuing_report.html

Since this checkup prints a part of the HTML source code of the data quality analysis output, the previously run step has exported data to this HTML file. These results can get reviewed in the HTML file together with other pipeline outputs.

It should contain the sample rate of 500 Hz of the original data. This sample rate allows for downsampling without loss of relevant data, since the highest frequency of interest is 12 Hz for later steps in this pipeline. With a theoretical, perfect low pass filter, sample rates above 24 Hz introduce redundancies between samples. To reduce this redundancy and decrease the computational effort, downsampling gets performed in a later step. There, additional descriptions follow.

Pre-processing: Skipped Steps¶

These two steps get ignored in the selected pipeline.

In [16]:
curr_steps = "preprocessing/_02_head_pos"
if curr_steps in STEPS_TO_RUN and STEPS_TO_RUN[curr_steps]:
    !mne_bids_pipeline --config {config_path} --steps {curr_steps}

┌────────┬ Welcome aboard MNE-BIDS-Pipeline! 👋 ────────────────────────────────
│22:40:02│ 📝 Using configuration: ./mne-bids/config/mne-bids-pipeline.py
└────────┴ 
┌────────┬ init/_01_init_derivatives_dir ───────────────────────────────────────
│22:40:02│ ✅ Output directories already exist …
└────────┴ done (1s)
┌────────┬ init/_02_find_empty_room ────────────────────────────────────────────
│22:40:02│ ⏩ Skipping, empty-room data only relevant for MEG …
└────────┴ done (1s)
┌────────┬ preprocessing/_02_head_pos ──────────────────────────────────────────
│22:40:02│ ⏩ Skipping …
└────────┴ done (1s)
In [17]:
# checkup: not needed, since this step was skipped
In [18]:
curr_steps = "preprocessing/_03_maxfilter"
if curr_steps in STEPS_TO_RUN and STEPS_TO_RUN[curr_steps]:
    !mne_bids_pipeline --config {config_path} --steps {curr_steps}

┌────────┬ Welcome aboard MNE-BIDS-Pipeline! 👋 ────────────────────────────────
│22:40:03│ 📝 Using configuration: ./mne-bids/config/mne-bids-pipeline.py
└────────┴ 
┌────────┬ init/_01_init_derivatives_dir ───────────────────────────────────────
│22:40:03│ ✅ Output directories already exist …
└────────┴ done (1s)
┌────────┬ init/_02_find_empty_room ────────────────────────────────────────────
│22:40:03│ ⏩ Skipping, empty-room data only relevant for MEG …
└────────┴ done (1s)
┌────────┬ preprocessing/_03_maxfilter ─────────────────────────────────────────
│22:40:03│ ⏩ Skipping …
└────────┴ done (1s)
In [19]:
# checkup: not needed, since this step was skipped

Pre-processing: Band Pass Filter etc.¶

The frequency filter step applies multiple linear, time invariant filters. An example is the applied band pass filter with cutoff frequencies at 1.0 Hz and 30.0 Hz. The lowpass filter removes most high frequency noise from the data, including D/C noise. The highpass filter does some implicit detrending, and is a good practice in preparation for the ICA artefact removal.

We decided for such a narrow filter band, as our analysis is based on more narrow bandwidths. These frequency bands in our analysis are alpha and theta oscillations. Both bands cutoff frequencies are in the range of 3 Hz to 12 Hz.

Thus, removing the energy of frequency bands below 1 Hz and above 30 Hz should not remove relevant information for this analysis. Furthermore, the lowpass frequency of 30 Hz allows for downsampling the signals with sample rates of at least 60 Hz.

This is based on the Nyquist theoreme: The sample rate should be at least twice as high as the highest frequency given in the signal. If this is not fulfilled, by aliasing the energy of the signal at frequencies higher than the Nyquist frequency gets added to the downsampled signal at other frequencies.

Since the filter curve is expected to be non-perfect in the sense of implementing a step from 0 dB amplification to -∞ dB at the cutoff frequency, a decreasing energy over the frequency above the cutoff frequency is expected. Based on this energy decay over the frequency, we chose a higher sample rate of 100 Hz to get a slightly improved signal to noise ratio compared to a lower sample rate.

The application of this pre-processing step is followed by a plot of the resulting spectral density of the power over the frequency for a single subject. This plot shows the effectiveness of the band pass filter. Additionally, the existence of the filtered signal file is proven.

In [20]:
curr_steps = "preprocessing/_04_frequency_filter"
if curr_steps in STEPS_TO_RUN and STEPS_TO_RUN[curr_steps]:
    !mne_bids_pipeline --config {config_path} --steps {curr_steps}

┌────────┬ Welcome aboard MNE-BIDS-Pipeline! 👋 ────────────────────────────────
│22:40:05│ 📝 Using configuration: ./mne-bids/config/mne-bids-pipeline.py
└────────┴ 
┌────────┬ init/_01_init_derivatives_dir ───────────────────────────────────────
│22:40:05│ ✅ Output directories already exist …
└────────┴ done (1s)
┌────────┬ init/_02_find_empty_room ────────────────────────────────────────────
│22:40:05│ ⏩ Skipping, empty-room data only relevant for MEG …
└────────┴ done (1s)
┌────────┬ preprocessing/_04_frequency_filter ──────────────────────────────────
│22:40:10│ ⏳️ sub-07 Setting EEG channel locations to template montage: standard_1005.
│22:40:10│ ⏳️ sub-07 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:40:11│ ⏳️ sub-02 Setting EEG channel locations to template montage: standard_1005.
│22:40:11│ ⏳️ sub-07 Renaming events …
│22:40:11│ ⏳️ sub-07 … s3021 -> avatar
│22:40:11│ ⏳️ sub-02 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:40:11│ ⏳️ sub-07 … s3041 -> sticks
│22:40:11│ ⏳️ sub-07 Not applying notch filter to experimental data.
│22:40:11│ ⏳️ sub-07 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:40:11│ ⏳️ sub-06 Setting EEG channel locations to template montage: standard_1005.
│22:40:11│ ⏳️ sub-06 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:40:11│ ⏳️ sub-01 Setting EEG channel locations to template montage: standard_1005.
│22:40:11│ ⏳️ sub-01 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:40:11│ ⏳️ sub-02 Renaming events …
│22:40:11│ ⏳️ sub-02 … s3021 -> avatar
│22:40:11│ ⏳️ sub-02 … s3041 -> sticks
│22:40:11│ ⏳️ sub-02 Not applying notch filter to experimental data.
│22:40:12│ ⏳️ sub-02 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:40:12│ ⏳️ sub-06 Renaming events …
│22:40:12│ ⏳️ sub-04 Setting EEG channel locations to template montage: standard_1005.
│22:40:12│ ⏳️ sub-06 … s3021 -> avatar
│22:40:12│ ⏳️ sub-06 … s3041 -> sticks
│22:40:12│ ⏳️ sub-04 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:40:12│ ⏳️ sub-06 Not applying notch filter to experimental data.
│22:40:12│ ⏳️ sub-06 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:40:12│ ⏳️ sub-01 Renaming events …
│22:40:12│ ⏳️ sub-01 … s3021 -> avatar
│22:40:12│ ⏳️ sub-01 … s3041 -> sticks
│22:40:12│ ⏳️ sub-01 Not applying notch filter to experimental data.
│22:40:12│ ⏳️ sub-01 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:40:12│ ⏳️ sub-03 Setting EEG channel locations to template montage: standard_1005.
│22:40:12│ ⏳️ sub-04 Renaming events …
│22:40:12│ ⏳️ sub-04 … s3021 -> avatar
│22:40:12│ ⏳️ sub-03 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:40:12│ ⏳️ sub-04 … s3041 -> sticks
│22:40:12│ ⏳️ sub-04 Not applying notch filter to experimental data.
│22:40:12│ ⏳️ sub-04 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:40:12│ ⏳️ sub-03 Renaming events …
│22:40:12│ ⏳️ sub-03 … s3021 -> avatar
│22:40:12│ ⏳️ sub-03 … s3041 -> sticks
│22:40:12│ ⏳️ sub-03 Not applying notch filter to experimental data.
│22:40:12│ ⏳️ sub-03 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:40:14│ ⏳️ sub-07 Resampling experimental data to 100.0 Hz
│22:40:15│ ⏳️ sub-02 Resampling experimental data to 100.0 Hz
│22:40:15│ ⏳️ sub-06 Resampling experimental data to 100.0 Hz
│22:40:15│ ⏳️ sub-01 Resampling experimental data to 100.0 Hz
│22:40:15│ ⏳️ sub-04 Resampling experimental data to 100.0 Hz
│22:40:18│ ⏳️ sub-03 Resampling experimental data to 100.0 Hz
│22:40:32│ ⏳️ sub-07 Adding filtered raw data to report
│22:40:34│ ⏳️ sub-02 Adding filtered raw data to report
│22:40:34│ ⏳️ sub-01 Adding filtered raw data to report
│22:40:34│ ⏳️ sub-06 Adding filtered raw data to report
│22:40:34│ ⏳️ sub-04 Adding filtered raw data to report
│22:40:35│ ⏳️ sub-03 Adding filtered raw data to report
│22:40:35│ ⏳️ sub-07 Adding config and sys info to report
│22:40:36│ ⏳️ sub-02 Adding config and sys info to report
│22:40:36│ ⏳️ sub-01 Adding config and sys info to report
│22:40:36│ ⏳️ sub-06 Adding config and sys info to report
│22:40:36│ ⏳️ sub-04 Adding config and sys info to report
│22:40:37│ ⏳️ sub-03 Adding config and sys info to report
│22:40:38│ ⏳️ sub-07 Saving report: ]8;id=627105;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=38108;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=625870;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\(]8;;\]8;id=533223;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=625870;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\)]8;;\]8;id=627105;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/]8;;\]8;id=38108;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\sub-07_task-SocialMemoryCuing_report.html]8;;\
│22:40:39│ ⏳️ sub-02 Saving report: ]8;id=114590;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=153594;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=944431;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\(]8;;\]8;id=175069;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=944431;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\)]8;;\]8;id=114590;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/]8;;\]8;id=153594;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\sub-02_task-SocialMemoryCuing_report.html]8;;\
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│22:40:40│ ⏳️ sub-09 Setting EEG channel locations to template montage: standard_1005.
│22:40:40│ ⏳️ sub-09 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
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│22:40:40│ ⏳️ sub-09 Renaming events …
│22:40:40│ ⏳️ sub-09 … s3021 -> avatar
│22:40:41│ ⏳️ sub-09 … s3041 -> sticks
│22:40:41│ ⏳️ sub-09 Not applying notch filter to experimental data.
│22:40:41│ ⏳️ sub-09 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:40:43│ ⏳️ sub-10 Setting EEG channel locations to template montage: standard_1005.
│22:40:43│ ⏳️ sub-10 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:40:43│ ⏳️ sub-12 Setting EEG channel locations to template montage: standard_1005.
│22:40:43│ ⏳️ sub-12 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:40:43│ ⏳️ sub-10 Renaming events …
│22:40:43│ ⏳️ sub-10 … s3021 -> avatar
│22:40:43│ ⏳️ sub-10 … s3041 -> sticks
│22:40:43│ ⏳️ sub-10 Not applying notch filter to experimental data.
│22:40:43│ ⏳️ sub-10 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:40:44│ ⏳️ sub-13 Setting EEG channel locations to template montage: standard_1005.
│22:40:44│ ⏳️ sub-13 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:40:44│ ⏳️ sub-12 Renaming events …
│22:40:44│ ⏳️ sub-11 Setting EEG channel locations to template montage: standard_1005.
│22:40:44│ ⏳️ sub-12 … s3021 -> avatar
│22:40:44│ ⏳️ sub-11 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:40:44│ ⏳️ sub-12 … s3041 -> sticks
│22:40:44│ ⏳️ sub-12 Not applying notch filter to experimental data.
│22:40:44│ ⏳️ sub-12 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:40:44│ ⏳️ sub-14 Setting EEG channel locations to template montage: standard_1005.
│22:40:44│ ⏳️ sub-13 Renaming events …
│22:40:44│ ⏳️ sub-13 … s3021 -> avatar
│22:40:44│ ⏳️ sub-14 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:40:44│ ⏳️ sub-13 … s3041 -> sticks
│22:40:44│ ⏳️ sub-13 Not applying notch filter to experimental data.
│22:40:44│ ⏳️ sub-13 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:40:44│ ⏳️ sub-11 Renaming events …
│22:40:44│ ⏳️ sub-11 … s3021 -> avatar
│22:40:45│ ⏳️ sub-11 … s3041 -> sticks
│22:40:45│ ⏳️ sub-11 Not applying notch filter to experimental data.
│22:40:45│ ⏳️ sub-11 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:40:45│ ⏳️ sub-14 Renaming events …
│22:40:45│ ⏳️ sub-14 … s3021 -> avatar
│22:40:45│ ⏳️ sub-14 … s3041 -> sticks
│22:40:45│ ⏳️ sub-14 Not applying notch filter to experimental data.
│22:40:45│ ⏳️ sub-14 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:40:46│ ⏳️ sub-09 Resampling experimental data to 100.0 Hz
│22:40:47│ ⏳️ sub-12 Resampling experimental data to 100.0 Hz
│22:40:47│ ⏳️ sub-10 Resampling experimental data to 100.0 Hz
│22:40:48│ ⏳️ sub-13 Resampling experimental data to 100.0 Hz
│22:40:49│ ⏳️ sub-14 Resampling experimental data to 100.0 Hz
│22:40:50│ ⏳️ sub-11 Resampling experimental data to 100.0 Hz
│22:41:04│ ⏳️ sub-09 Adding filtered raw data to report
│22:41:07│ ⏳️ sub-12 Adding filtered raw data to report
│22:41:07│ ⏳️ sub-09 Adding config and sys info to report
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│22:41:08│ ⏳️ sub-10 Adding filtered raw data to report
│22:41:08│ ⏳️ sub-13 Adding filtered raw data to report
│22:41:08│ ⏳️ sub-14 Adding filtered raw data to report
│22:41:08│ ⏳️ sub-11 Adding filtered raw data to report
│22:41:09│ ⏳️ sub-12 Adding config and sys info to report
│22:41:09│ ⏳️ sub-12 Saving report: ]8;id=936624;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=626556;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=929013;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\(]8;;\]8;id=673542;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=929013;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\)]8;;\]8;id=936624;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/]8;;\]8;id=626556;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\sub-12_task-SocialMemoryCuing_report.html]8;;\
│22:41:10│ ⏳️ sub-15 Setting EEG channel locations to template montage: standard_1005.
│22:41:10│ ⏳️ sub-15 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:41:10│ ⏳️ sub-14 Adding config and sys info to report
│22:41:10│ ⏳️ sub-14 Saving report: ]8;id=772483;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=307904;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=495660;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\(]8;;\]8;id=235240;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=495660;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\)]8;;\]8;id=772483;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/]8;;\]8;id=307904;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\sub-14_task-SocialMemoryCuing_report.html]8;;\
│22:41:10│ ⏳️ sub-13 Adding config and sys info to report
│22:41:10│ ⏳️ sub-13 Saving report: ]8;id=294991;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=655956;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=32592;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\(]8;;\]8;id=565088;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=32592;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\)]8;;\]8;id=294991;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/]8;;\]8;id=655956;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\sub-13_task-SocialMemoryCuing_report.html]8;;\
│22:41:10│ ⏳️ sub-10 Adding config and sys info to report
│22:41:10│ ⏳️ sub-10 Saving report: ]8;id=558405;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=982983;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=604565;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\(]8;;\]8;id=80003;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=604565;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\)]8;;\]8;id=558405;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/]8;;\]8;id=982983;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\sub-10_task-SocialMemoryCuing_report.html]8;;\
│22:41:10│ ⏳️ sub-15 Renaming events …
│22:41:10│ ⏳️ sub-15 … s3021 -> avatar
│22:41:10│ ⏳️ sub-15 … s3041 -> sticks
│22:41:10│ ⏳️ sub-15 Not applying notch filter to experimental data.
│22:41:10│ ⏳️ sub-15 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:41:11│ ⏳️ sub-11 Adding config and sys info to report
│22:41:11│ ⏳️ sub-11 Saving report: ]8;id=863250;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=732530;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=572401;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\(]8;;\]8;id=852443;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=572401;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\)]8;;\]8;id=863250;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/]8;;\]8;id=732530;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\sub-11_task-SocialMemoryCuing_report.html]8;;\
│22:41:13│ ⏳️ sub-16 Setting EEG channel locations to template montage: standard_1005.
│22:41:13│ ⏳️ sub-16 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:41:14│ ⏳️ sub-19 Setting EEG channel locations to template montage: standard_1005.
│22:41:14│ ⏳️ sub-19 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:41:14│ ⏳️ sub-17 Setting EEG channel locations to template montage: standard_1005.
│22:41:14│ ⏳️ sub-18 Setting EEG channel locations to template montage: standard_1005.
│22:41:14│ ⏳️ sub-17 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:41:14│ ⏳️ sub-16 Renaming events …
│22:41:14│ ⏳️ sub-18 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:41:14│ ⏳️ sub-16 … s3021 -> avatar
│22:41:14│ ⏳️ sub-16 … s3041 -> sticks
│22:41:14│ ⏳️ sub-16 Not applying notch filter to experimental data.
│22:41:14│ ⏳️ sub-16 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:41:14│ ⏳️ sub-19 Renaming events …
│22:41:14│ ⏳️ sub-19 … s3021 -> avatar
│22:41:14│ ⏳️ sub-19 … s3041 -> sticks
│22:41:14│ ⏳️ sub-19 Not applying notch filter to experimental data.
│22:41:14│ ⏳️ sub-19 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:41:15│ ⏳️ sub-18 Renaming events …
│22:41:15│ ⏳️ sub-18 … s3021 -> avatar
│22:41:15│ ⏳️ sub-18 … s3041 -> sticks
│22:41:15│ ⏳️ sub-17 Renaming events …
│22:41:15│ ⏳️ sub-18 Not applying notch filter to experimental data.
│22:41:15│ ⏳️ sub-18 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:41:15│ ⏳️ sub-17 … s3021 -> avatar
│22:41:15│ ⏳️ sub-17 … s3041 -> sticks
│22:41:15│ ⏳️ sub-17 Not applying notch filter to experimental data.
│22:41:15│ ⏳️ sub-17 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:41:15│ ⏳️ sub-15 Resampling experimental data to 100.0 Hz
│22:41:15│ ⏳️ sub-21 Setting EEG channel locations to template montage: standard_1005.
│22:41:15│ ⏳️ sub-21 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:41:15│ ⏳️ sub-21 Renaming events …
│22:41:15│ ⏳️ sub-21 … s3021 -> avatar
│22:41:15│ ⏳️ sub-21 … s3041 -> sticks
│22:41:15│ ⏳️ sub-21 Not applying notch filter to experimental data.
│22:41:15│ ⏳️ sub-21 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:41:18│ ⏳️ sub-16 Resampling experimental data to 100.0 Hz
│22:41:18│ ⏳️ sub-19 Resampling experimental data to 100.0 Hz
│22:41:19│ ⏳️ sub-18 Resampling experimental data to 100.0 Hz
│22:41:19│ ⏳️ sub-17 Resampling experimental data to 100.0 Hz
│22:41:19│ ⏳️ sub-21 Resampling experimental data to 100.0 Hz
│22:41:29│ ⏳️ sub-15 Adding filtered raw data to report
│22:41:33│ ⏳️ sub-15 Adding config and sys info to report
│22:41:33│ ⏳️ sub-15 Saving report: ]8;id=289129;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=455028;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=823108;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\(]8;;\]8;id=818642;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=823108;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\)]8;;\]8;id=289129;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/]8;;\]8;id=455028;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\sub-15_task-SocialMemoryCuing_report.html]8;;\
│22:41:37│ ⏳️ sub-16 Adding filtered raw data to report
│22:41:37│ ⏳️ sub-22 Setting EEG channel locations to template montage: standard_1005.
│22:41:37│ ⏳️ sub-19 Adding filtered raw data to report
│22:41:37│ ⏳️ sub-22 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:41:37│ ⏳️ sub-18 Adding filtered raw data to report
│22:41:37│ ⏳️ sub-17 Adding filtered raw data to report
│22:41:37│ ⏳️ sub-21 Adding filtered raw data to report
│22:41:38│ ⏳️ sub-22 Renaming events …
│22:41:38│ ⏳️ sub-22 … s3021 -> avatar
│22:41:38│ ⏳️ sub-22 … s3041 -> sticks
│22:41:38│ ⏳️ sub-22 Not applying notch filter to experimental data.
│22:41:38│ ⏳️ sub-22 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:41:39│ ⏳️ sub-16 Adding config and sys info to report
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│22:41:39│ ⏳️ sub-19 Adding config and sys info to report
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│22:41:40│ ⏳️ sub-21 Adding config and sys info to report
│22:41:40│ ⏳️ sub-18 Adding config and sys info to report
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│22:41:40│ ⏳️ sub-18 Saving report: ]8;id=527340;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=647037;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=98029;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\(]8;;\]8;id=775208;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=98029;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\)]8;;\]8;id=527340;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/]8;;\]8;id=647037;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\sub-18_task-SocialMemoryCuing_report.html]8;;\
│22:41:40│ ⏳️ sub-17 Adding config and sys info to report
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│22:41:42│ ⏳️ sub-23 Setting EEG channel locations to template montage: standard_1005.
│22:41:42│ ⏳️ sub-23 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:41:42│ ⏳️ sub-22 Resampling experimental data to 100.0 Hz
│22:41:43│ ⏳️ sub-23 Renaming events …
│22:41:43│ ⏳️ sub-23 … s3021 -> avatar
│22:41:43│ ⏳️ sub-23 … s3041 -> sticks
│22:41:43│ ⏳️ sub-23 Not applying notch filter to experimental data.
│22:41:43│ ⏳️ sub-23 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:41:44│ ⏳️ sub-27 Setting EEG channel locations to template montage: standard_1005.
│22:41:44│ ⏳️ sub-27 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:41:44│ ⏳️ sub-25 Setting EEG channel locations to template montage: standard_1005.
│22:41:44│ ⏳️ sub-25 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:41:44│ ⏳️ sub-24 Setting EEG channel locations to template montage: standard_1005.
│22:41:44│ ⏳️ sub-24 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:41:44│ ⏳️ sub-26 Setting EEG channel locations to template montage: standard_1005.
│22:41:44│ ⏳️ sub-26 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:41:44│ ⏳️ sub-27 Renaming events …
│22:41:44│ ⏳️ sub-25 Renaming events …
│22:41:44│ ⏳️ sub-27 … s3021 -> avatar
│22:41:44│ ⏳️ sub-25 … s3021 -> avatar
│22:41:44│ ⏳️ sub-25 … s3041 -> sticks
│22:41:44│ ⏳️ sub-27 … s3041 -> sticks
│22:41:44│ ⏳️ sub-25 Not applying notch filter to experimental data.
│22:41:44│ ⏳️ sub-27 Not applying notch filter to experimental data.
│22:41:44│ ⏳️ sub-25 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:41:44│ ⏳️ sub-27 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:41:45│ ⏳️ sub-24 Renaming events …
│22:41:45│ ⏳️ sub-24 … s3021 -> avatar
│22:41:45│ ⏳️ sub-24 … s3041 -> sticks
│22:41:45│ ⏳️ sub-24 Not applying notch filter to experimental data.
│22:41:45│ ⏳️ sub-24 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:41:45│ ⏳️ sub-26 Renaming events …
│22:41:45│ ⏳️ sub-26 … s3021 -> avatar
│22:41:45│ ⏳️ sub-26 … s3041 -> sticks
│22:41:45│ ⏳️ sub-26 Not applying notch filter to experimental data.
│22:41:45│ ⏳️ sub-26 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:41:47│ ⏳️ sub-23 Resampling experimental data to 100.0 Hz
│22:41:48│ ⏳️ sub-27 Resampling experimental data to 100.0 Hz
│22:41:48│ ⏳️ sub-25 Resampling experimental data to 100.0 Hz
│22:41:49│ ⏳️ sub-24 Resampling experimental data to 100.0 Hz
│22:41:50│ ⏳️ sub-26 Resampling experimental data to 100.0 Hz
│22:41:57│ ⏳️ sub-22 Adding filtered raw data to report
│22:42:01│ ⏳️ sub-22 Adding config and sys info to report
│22:42:01│ ⏳️ sub-22 Saving report: ]8;id=624586;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=141604;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=141038;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\(]8;;\]8;id=334605;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=141038;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\)]8;;\]8;id=624586;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/]8;;\]8;id=141604;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\sub-22_task-SocialMemoryCuing_report.html]8;;\
│22:42:04│ ⏳️ sub-23 Adding filtered raw data to report
│22:42:05│ ⏳️ sub-28 Setting EEG channel locations to template montage: standard_1005.
│22:42:05│ ⏳️ sub-28 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:42:05│ ⏳️ sub-28 Renaming events …
│22:42:05│ ⏳️ sub-28 … s3021 -> avatar
│22:42:05│ ⏳️ sub-28 … s3041 -> sticks
│22:42:05│ ⏳️ sub-28 Not applying notch filter to experimental data.
│22:42:05│ ⏳️ sub-28 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:42:06│ ⏳️ sub-27 Adding filtered raw data to report
│22:42:06│ ⏳️ sub-25 Adding filtered raw data to report
│22:42:06│ ⏳️ sub-24 Adding filtered raw data to report
│22:42:07│ ⏳️ sub-26 Adding filtered raw data to report
│22:42:07│ ⏳️ sub-23 Adding config and sys info to report
│22:42:07│ ⏳️ sub-23 Saving report: ]8;id=99957;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=972995;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=718987;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\(]8;;\]8;id=267691;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=718987;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\)]8;;\]8;id=99957;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/]8;;\]8;id=972995;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\sub-23_task-SocialMemoryCuing_report.html]8;;\
│22:42:08│ ⏳️ sub-28 Resampling experimental data to 100.0 Hz
│22:42:08│ ⏳️ sub-27 Adding config and sys info to report
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│22:42:08│ ⏳️ sub-25 Adding config and sys info to report
│22:42:08│ ⏳️ sub-25 Saving report: ]8;id=805219;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=319885;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=340908;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\(]8;;\]8;id=941124;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=340908;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\)]8;;\]8;id=805219;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/]8;;\]8;id=319885;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\sub-25_task-SocialMemoryCuing_report.html]8;;\
│22:42:09│ ⏳️ sub-24 Adding config and sys info to report
│22:42:09│ ⏳️ sub-24 Saving report: ]8;id=833680;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=162613;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=315223;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\(]8;;\]8;id=567565;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=315223;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\)]8;;\]8;id=833680;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/]8;;\]8;id=162613;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\sub-24_task-SocialMemoryCuing_report.html]8;;\
│22:42:09│ ⏳️ sub-30 Setting EEG channel locations to template montage: standard_1005.
│22:42:09│ ⏳️ sub-30 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:42:10│ ⏳️ sub-30 Renaming events …
│22:42:10│ ⏳️ sub-30 … s3021 -> avatar
│22:42:10│ ⏳️ sub-30 … s3041 -> sticks
│22:42:10│ ⏳️ sub-30 Not applying notch filter to experimental data.
│22:42:10│ ⏳️ sub-30 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:42:10│ ⏳️ sub-26 Adding config and sys info to report
│22:42:10│ ⏳️ sub-26 Saving report: ]8;id=498583;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=949397;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=867251;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\(]8;;\]8;id=380438;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=867251;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\)]8;;\]8;id=498583;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/]8;;\]8;id=949397;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\sub-26_task-SocialMemoryCuing_report.html]8;;\
│22:42:11│ ⏳️ sub-32 Setting EEG channel locations to template montage: standard_1005.
│22:42:11│ ⏳️ sub-32 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:42:12│ ⏳️ sub-33 Setting EEG channel locations to template montage: standard_1005.
│22:42:12│ ⏳️ sub-33 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:42:12│ ⏳️ sub-34 Setting EEG channel locations to template montage: standard_1005.
│22:42:12│ ⏳️ sub-34 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:42:12│ ⏳️ sub-32 Renaming events …
│22:42:12│ ⏳️ sub-32 … s3021 -> avatar
│22:42:12│ ⏳️ sub-32 … s3041 -> sticks
│22:42:12│ ⏳️ sub-32 Not applying notch filter to experimental data.
│22:42:12│ ⏳️ sub-32 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:42:12│ ⏳️ sub-33 Renaming events …
│22:42:12│ ⏳️ sub-33 … s3021 -> avatar
│22:42:12│ ⏳️ sub-33 … s3041 -> sticks
│22:42:12│ ⏳️ sub-33 Not applying notch filter to experimental data.
│22:42:13│ ⏳️ sub-34 Renaming events …
│22:42:13│ ⏳️ sub-34 … s3021 -> avatar
│22:42:13│ ⏳️ sub-33 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:42:13│ ⏳️ sub-34 … s3041 -> sticks
│22:42:13│ ⏳️ sub-34 Not applying notch filter to experimental data.
│22:42:13│ ⏳️ sub-34 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:42:14│ ⏳️ sub-30 Resampling experimental data to 100.0 Hz
│22:42:15│ ⏳️ sub-35 Setting EEG channel locations to template montage: standard_1005.
│22:42:15│ ⏳️ sub-35 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:42:15│ ⏳️ sub-35 Renaming events …
│22:42:15│ ⏳️ sub-35 … s3021 -> avatar
│22:42:15│ ⏳️ sub-35 … s3041 -> sticks
│22:42:16│ ⏳️ sub-35 Not applying notch filter to experimental data.
│22:42:16│ ⏳️ sub-35 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:42:16│ ⏳️ sub-32 Resampling experimental data to 100.0 Hz
│22:42:17│ ⏳️ sub-34 Resampling experimental data to 100.0 Hz
│22:42:18│ ⏳️ sub-33 Resampling experimental data to 100.0 Hz
│22:42:23│ ⏳️ sub-35 Resampling experimental data to 100.0 Hz
│22:42:23│ ⏳️ sub-28 Adding filtered raw data to report
│22:42:27│ ⏳️ sub-28 Adding config and sys info to report
│22:42:27│ ⏳️ sub-28 Saving report: ]8;id=857361;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=203469;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=383202;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\(]8;;\]8;id=301165;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=383202;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\)]8;;\]8;id=857361;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/]8;;\]8;id=203469;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\sub-28_task-SocialMemoryCuing_report.html]8;;\
│22:42:32│ ⏳️ sub-38 Setting EEG channel locations to template montage: standard_1005.
│22:42:32│ ⏳️ sub-30 Adding filtered raw data to report
│22:42:32│ ⏳️ sub-38 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:42:32│ ⏳️ sub-38 Renaming events …
│22:42:32│ ⏳️ sub-38 … s3021 -> avatar
│22:42:32│ ⏳️ sub-38 … s3041 -> sticks
│22:42:32│ ⏳️ sub-38 Not applying notch filter to experimental data.
│22:42:32│ ⏳️ sub-38 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:42:33│ ⏳️ sub-32 Adding filtered raw data to report
│22:42:34│ ⏳️ sub-34 Adding filtered raw data to report
│22:42:35│ ⏳️ sub-30 Adding config and sys info to report
│22:42:35│ ⏳️ sub-30 Saving report: ]8;id=944899;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=968417;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=810079;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\(]8;;\]8;id=226887;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=810079;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\)]8;;\]8;id=944899;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/]8;;\]8;id=968417;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\sub-30_task-SocialMemoryCuing_report.html]8;;\
│22:42:35│ ⏳️ sub-33 Adding filtered raw data to report
│22:42:36│ ⏳️ sub-32 Adding config and sys info to report
│22:42:36│ ⏳️ sub-32 Saving report: ]8;id=172261;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=981007;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=267876;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\(]8;;\]8;id=356249;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=267876;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\)]8;;\]8;id=172261;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/]8;;\]8;id=981007;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\sub-32_task-SocialMemoryCuing_report.html]8;;\
│22:42:36│ ⏳️ sub-38 Resampling experimental data to 100.0 Hz
│22:42:38│ ⏳️ sub-34 Adding config and sys info to report
│22:42:38│ ⏳️ sub-34 Saving report: ]8;id=61803;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=837475;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=915515;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\(]8;;\]8;id=520700;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=915515;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\)]8;;\]8;id=61803;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/]8;;\]8;id=837475;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\sub-34_task-SocialMemoryCuing_report.html]8;;\
│22:42:38│ ⏳️ sub-39 Setting EEG channel locations to template montage: standard_1005.
│22:42:38│ ⏳️ sub-39 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:42:38│ ⏳️ sub-35 Adding filtered raw data to report
│22:42:38│ ⏳️ sub-33 Adding config and sys info to report
│22:42:38│ ⏳️ sub-33 Saving report: ]8;id=332144;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=97766;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=853085;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\(]8;;\]8;id=571166;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=853085;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\)]8;;\]8;id=332144;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/]8;;\]8;id=97766;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\sub-33_task-SocialMemoryCuing_report.html]8;;\
│22:42:38│ ⏳️ sub-39 Renaming events …
│22:42:38│ ⏳️ sub-39 … s3021 -> avatar
│22:42:38│ ⏳️ sub-39 … s3041 -> sticks
│22:42:38│ ⏳️ sub-39 Not applying notch filter to experimental data.
│22:42:38│ ⏳️ sub-39 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:42:39│ ⏳️ sub-40 Setting EEG channel locations to template montage: standard_1005.
│22:42:39│ ⏳️ sub-40 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:42:40│ ⏳️ sub-40 Renaming events …
│22:42:40│ ⏳️ sub-40 … s3021 -> avatar
│22:42:40│ ⏳️ sub-40 … s3041 -> sticks
│22:42:40│ ⏳️ sub-40 Not applying notch filter to experimental data.
│22:42:40│ ⏳️ sub-40 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:42:41│ ⏳️ sub-43 Setting EEG channel locations to template montage: standard_1005.
│22:42:41│ ⏳️ sub-43 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:42:41│ ⏳️ sub-41 Setting EEG channel locations to template montage: standard_1005.
│22:42:41│ ⏳️ sub-41 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:42:41│ ⏳️ sub-43 Renaming events …
│22:42:41│ ⏳️ sub-43 … s3021 -> avatar
│22:42:41│ ⏳️ sub-43 … s3041 -> sticks
│22:42:41│ ⏳️ sub-43 Not applying notch filter to experimental data.
│22:42:41│ ⏳️ sub-43 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:42:42│ ⏳️ sub-35 Adding config and sys info to report
│22:42:42│ ⏳️ sub-35 Saving report: ]8;id=630979;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=306443;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=438946;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\(]8;;\]8;id=928446;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=438946;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\)]8;;\]8;id=630979;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/]8;;\]8;id=306443;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\sub-35_task-SocialMemoryCuing_report.html]8;;\
│22:42:42│ ⏳️ sub-41 Renaming events …
│22:42:42│ ⏳️ sub-41 … s3021 -> avatar
│22:42:42│ ⏳️ sub-41 … s3041 -> sticks
│22:42:42│ ⏳️ sub-41 Not applying notch filter to experimental data.
│22:42:42│ ⏳️ sub-41 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:42:43│ ⏳️ sub-39 Resampling experimental data to 100.0 Hz
│22:42:44│ ⏳️ sub-40 Resampling experimental data to 100.0 Hz
│22:42:45│ ⏳️ sub-44 Setting EEG channel locations to template montage: standard_1005.
│22:42:45│ ⏳️ sub-44 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:42:45│ ⏳️ sub-44 Renaming events …
│22:42:45│ ⏳️ sub-44 … s3021 -> avatar
│22:42:45│ ⏳️ sub-44 … s3041 -> sticks
│22:42:45│ ⏳️ sub-44 Not applying notch filter to experimental data.
│22:42:45│ ⏳️ sub-44 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:42:46│ ⏳️ sub-43 Resampling experimental data to 100.0 Hz
│22:42:47│ ⏳️ sub-41 Resampling experimental data to 100.0 Hz
│22:42:49│ ⏳️ sub-38 Adding filtered raw data to report
│22:42:51│ ⏳️ sub-44 Resampling experimental data to 100.0 Hz
│22:42:53│ ⏳️ sub-38 Adding config and sys info to report
│22:42:53│ ⏳️ sub-38 Saving report: ]8;id=297025;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=1002;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=594879;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\(]8;;\]8;id=589790;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=594879;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\)]8;;\]8;id=297025;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/]8;;\]8;id=1002;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\sub-38_task-SocialMemoryCuing_report.html]8;;\
│22:42:57│ ⏳️ sub-45 Setting EEG channel locations to template montage: standard_1005.
│22:42:57│ ⏳️ sub-45 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:42:58│ ⏳️ sub-45 Renaming events …
│22:42:58│ ⏳️ sub-45 … s3021 -> avatar
│22:42:58│ ⏳️ sub-45 … s3041 -> sticks
│22:42:58│ ⏳️ sub-45 Not applying notch filter to experimental data.
│22:42:58│ ⏳️ sub-45 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:42:59│ ⏳️ sub-39 Adding filtered raw data to report
│22:43:02│ ⏳️ sub-40 Adding filtered raw data to report
│22:43:02│ ⏳️ sub-43 Adding filtered raw data to report
│22:43:02│ ⏳️ sub-45 Resampling experimental data to 100.0 Hz
│22:43:03│ ⏳️ sub-39 Adding config and sys info to report
│22:43:03│ ⏳️ sub-39 Saving report: ]8;id=993185;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=644521;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=710786;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\(]8;;\]8;id=783268;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=710786;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\)]8;;\]8;id=993185;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/]8;;\]8;id=644521;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\sub-39_task-SocialMemoryCuing_report.html]8;;\
│22:43:03│ ⏳️ sub-41 Adding filtered raw data to report
│22:43:05│ ⏳️ sub-40 Adding config and sys info to report
│22:43:05│ ⏳️ sub-40 Saving report: ]8;id=261759;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=258166;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=40231;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\(]8;;\]8;id=840636;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=40231;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\)]8;;\]8;id=261759;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/]8;;\]8;id=258166;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\sub-40_task-SocialMemoryCuing_report.html]8;;\
│22:43:05│ ⏳️ sub-43 Adding config and sys info to report
│22:43:05│ ⏳️ sub-43 Saving report: ]8;id=687007;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=342316;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=874664;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\(]8;;\]8;id=105528;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=874664;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\)]8;;\]8;id=687007;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/]8;;\]8;id=342316;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\sub-43_task-SocialMemoryCuing_report.html]8;;\
│22:43:05│ ⏳️ sub-44 Adding filtered raw data to report
│22:43:06│ ⏳️ sub-46 Setting EEG channel locations to template montage: standard_1005.
│22:43:06│ ⏳️ sub-46 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:43:06│ ⏳️ sub-41 Adding config and sys info to report
│22:43:06│ ⏳️ sub-41 Saving report: ]8;id=600056;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=878755;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=681296;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\(]8;;\]8;id=815952;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=681296;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\)]8;;\]8;id=600056;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/]8;;\]8;id=878755;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\sub-41_task-SocialMemoryCuing_report.html]8;;\
│22:43:06│ ⏳️ sub-46 Renaming events …
│22:43:06│ ⏳️ sub-46 … s3021 -> avatar
│22:43:06│ ⏳️ sub-46 … s3041 -> sticks
│22:43:06│ ⏳️ sub-46 Not applying notch filter to experimental data.
│22:43:06│ ⏳️ sub-46 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:43:08│ ⏳️ sub-48 Setting EEG channel locations to template montage: standard_1005.
│22:43:08│ ⏳️ sub-48 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:43:09│ ⏳️ sub-49 Setting EEG channel locations to template montage: standard_1005.
│22:43:09│ ⏳️ sub-49 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:43:09│ ⏳️ sub-44 Adding config and sys info to report
│22:43:09│ ⏳️ sub-44 Saving report: ]8;id=451291;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=4345;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=549741;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\(]8;;\]8;id=674095;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=549741;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\)]8;;\]8;id=451291;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/]8;;\]8;id=4345;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\sub-44_task-SocialMemoryCuing_report.html]8;;\
│22:43:09│ ⏳️ sub-48 Renaming events …
│22:43:09│ ⏳️ sub-48 … s3021 -> avatar
│22:43:09│ ⏳️ sub-48 … s3041 -> sticks
│22:43:09│ ⏳️ sub-48 Not applying notch filter to experimental data.
│22:43:09│ ⏳️ sub-48 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:43:09│ ⏳️ sub-49 Renaming events …
│22:43:09│ ⏳️ sub-49 … s3021 -> avatar
│22:43:09│ ⏳️ sub-49 … s3041 -> sticks
│22:43:09│ ⏳️ sub-49 Not applying notch filter to experimental data.
│22:43:09│ ⏳️ sub-49 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:43:10│ ⏳️ sub-50 Setting EEG channel locations to template montage: standard_1005.
│22:43:10│ ⏳️ sub-50 Dropping channels: EOG, BIP1, BIP2, BIP3, BIP4, BIP5, BIP6, BIP7, BIP8, BIP9, BIP10, BIP11, BIP12, BIP13, BIP14, BIP15, BIP16, BIP17, BIP18, BIP19, BIP20, BIP21, BIP22, BIP23, BIP24
│22:43:10│ ⏳️ sub-50 Renaming events …
│22:43:10│ ⏳️ sub-50 … s3021 -> avatar
│22:43:10│ ⏳️ sub-50 … s3041 -> sticks
│22:43:10│ ⏳️ sub-50 Not applying notch filter to experimental data.
│22:43:10│ ⏳️ sub-50 Band-pass filtering experimental data; range: 1.0 – 30.0 Hz
│22:43:10│ ⏳️ sub-46 Resampling experimental data to 100.0 Hz
│22:43:13│ ⏳️ sub-48 Resampling experimental data to 100.0 Hz
│22:43:13│ ⏳️ sub-45 Adding filtered raw data to report
│22:43:13│ ⏳️ sub-49 Resampling experimental data to 100.0 Hz
│22:43:14│ ⏳️ sub-50 Resampling experimental data to 100.0 Hz
│22:43:16│ ⏳️ sub-45 Adding config and sys info to report
│22:43:16│ ⏳️ sub-45 Saving report: ]8;id=247600;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=278234;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=13181;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\(]8;;\]8;id=31915;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=13181;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\)]8;;\]8;id=247600;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/]8;;\]8;id=278234;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\sub-45_task-SocialMemoryCuing_report.html]8;;\
│22:43:22│ ⏳️ sub-46 Adding filtered raw data to report
│22:43:24│ ⏳️ sub-48 Adding filtered raw data to report
│22:43:24│ ⏳️ sub-46 Adding config and sys info to report
│22:43:24│ ⏳️ sub-46 Saving report: ]8;id=24981;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=354859;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=168857;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\(]8;;\]8;id=444412;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=168857;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\)]8;;\]8;id=24981;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/]8;;\]8;id=354859;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\sub-46_task-SocialMemoryCuing_report.html]8;;\
│22:43:24│ ⏳️ sub-49 Adding filtered raw data to report
│22:43:25│ ⏳️ sub-50 Adding filtered raw data to report
│22:43:26│ ⏳️ sub-48 Adding config and sys info to report
│22:43:26│ ⏳️ sub-48 Saving report: ]8;id=661039;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=131325;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=471442;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\(]8;;\]8;id=841822;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=471442;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\)]8;;\]8;id=661039;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/]8;;\]8;id=131325;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\sub-48_task-SocialMemoryCuing_report.html]8;;\
│22:43:26│ ⏳️ sub-49 Adding config and sys info to report
│22:43:26│ ⏳️ sub-49 Saving report: ]8;id=392632;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=731414;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=477925;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\(]8;;\]8;id=620435;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=477925;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\)]8;;\]8;id=392632;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/]8;;\]8;id=731414;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\sub-49_task-SocialMemoryCuing_report.html]8;;\
│22:43:26│ ⏳️ sub-50 Adding config and sys info to report
│22:43:26│ ⏳️ sub-50 Saving report: ]8;id=4598;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=914675;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=907152;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\(]8;;\]8;id=221329;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=907152;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\)]8;;\]8;id=4598;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/]8;;\]8;id=914675;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\sub-50_task-SocialMemoryCuing_report.html]8;;\
└────────┴ done (3m 22s)

To check for a successful application of the bandpass filter, the power spectral density of the filtered signal gets plotted.

In [ ]:
In [ ]:
In [68]:
# checkup: print spectrum of original and filtered signals, print sample rate of new raw data file
curr_checkup_subject_id = "01" # For subject 4, the signals seem to be less noisy, but for historical reasons subject 1 remains chosen.
curr_checkup_filename = f"{curr_bids_root}/derivatives/mne-bids-pipeline/sub-{curr_checkup_subject_id}/eeg/sub-{curr_checkup_subject_id}_task-SocialMemoryCuing_proc-filt_raw.fif"
curr_checkup_raw_filtered = mne.io.read_raw_fif(curr_checkup_filename, preload=True)
curr_checkup_raw_filtered.plot_psd()
print("checkup plot showing reduced bandwidth of eeg signals")

/opt/venv/eeg/lib/python3.11/site-packages/mne/viz/utils.py:165: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown
  (fig or plt).show(**kwargs)

checkup plot showing reduced bandwidth of eeg signals
No description has been provided for this image

This checkup shows multiple results:

  • For low frequencies, the power per frequency bin gets reduced by approximately 30-40 dB between 1 Hz and 0 Hz compared to constant power over frequency.
    • ⇒ The high pass filter seems to work.
  • For high frequencies, the power per frequency bin gets reduced by about 60 dB compared to constant power over frequency in a third octave above the upper cutoff frequency at 30 Hz.
    • ⇒ The low pass filter seems to work.
  • The 2d electrode position map (top right corner) seems to be somewhat valid.
    • ⇒ The electrode positions seem to be loaded correctly.
  • The spectral power density seems to be similar for all electrodes for this subject.
    • ⇒ At first glance, the electrodes seem to have been mounted in a similar way. This could indicate a correct use of the EEG measurement technology by trained personal.
In [23]:
# checkup: print file name if the processed file exists
curr_subject_path = f"{curr_bids_root}/derivatives/mne-bids-pipeline/sub-01/eeg"
cmd.ls(curr_subject_path + "/sub-01_task-SocialMemoryCuing_proc-filt_raw.fif")

sub-01_task-SocialMemoryCuing_proc-filt_raw.fif

The file seems to exist. This indicates a correctly downloaded and extracted dataset at the expected path.

Pre-processing: Split Signal to Epochs¶

In the next step, the signal gets split to epochs per subject. This extraction is followed by the plot of all epochs of an example subject.

The epochs start one second before the cue object appears, and end them seven seconds later. Therefore, the time interval is -1.0 to 6.0 seconds relative to the cue appearance.

The epochs contain multiple time frames:

  • The baseline of 1 second (-1s to 0s),
  • the cue pointing downwards (0s to 1.5s),
  • the cue shifting upwards (1.5s to 2s),
  • the cue "looking" at the subject directly (2s to 3s),
  • the cue shifting left or right (3s to 3.5s), and
  • the memory targets being shown (3.5s to 4s).

Since the content of these two seconds are not relevant for the main research question, they are removed from the interval:

  • maintenance interval (4s to 5s), and
  • showing of the location target to the subject (5s to 6s)

This results in the shortened interval of 5 seconds of -1 second to +4 seconds relative to the cue object appearance. In addition to better focus on the more relevant data, the shortened duration should reduce the processing time by two in seven parts. This equals an expected increased processing speed by 28.6 % based on the number of to-be-processed samples.

In [24]:
curr_steps = "preprocessing/_05_make_epochs"
if curr_steps in STEPS_TO_RUN and STEPS_TO_RUN[curr_steps]:
    !mne_bids_pipeline --config {config_path} --steps {curr_steps}

┌────────┬ Welcome aboard MNE-BIDS-Pipeline! 👋 ────────────────────────────────
│22:43:31│ 📝 Using configuration: ./mne-bids/config/mne-bids-pipeline.py
└────────┴ 
┌────────┬ init/_01_init_derivatives_dir ───────────────────────────────────────
│22:43:31│ ✅ Output directories already exist …
└────────┴ done (1s)
┌────────┬ init/_02_find_empty_room ────────────────────────────────────────────
│22:43:31│ ⏩ Skipping, empty-room data only relevant for MEG …
└────────┴ done (1s)
┌────────┬ preprocessing/_05_make_epochs ───────────────────────────────────────
│22:43:33│ ⏳️ sub-01 Loading filtered raw data from sub-01_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:33│ ⏳️ sub-01 Creating task-related epochs …
│22:43:33│ ⏳️ sub-07 Loading filtered raw data from sub-07_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:33│ ⏳️ sub-02 Loading filtered raw data from sub-02_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:33│ ⏳️ sub-06 Loading filtered raw data from sub-06_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:33│ ⏳️ sub-04 Loading filtered raw data from sub-04_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:33│ ⏳️ sub-07 Creating task-related epochs …
│22:43:33│ ⏳️ sub-02 Creating task-related epochs …
│22:43:33│ ⏳️ sub-06 Creating task-related epochs …
│22:43:33│ ⏳️ sub-03 Loading filtered raw data from sub-03_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:34│ ⏳️ sub-04 Creating task-related epochs …
│22:43:34│ ⏳️ sub-03 Creating task-related epochs …
│22:43:36│ ⏳️ sub-02 Created 216 epochs with time interval: -1.0 – 4.0 sec.
│22:43:36│ ⏳️ sub-02 Selected 216 epochs via metadata query: None
│22:43:36│ ⏳️ sub-02 Writing 216 epochs to disk.
│22:43:37│ ⏳️ sub-02 Adding events plot to report.
│22:43:37│ ⏳️ sub-01 Created 232 epochs with time interval: -1.0 – 4.0 sec.
│22:43:37│ ⏳️ sub-01 Selected 232 epochs via metadata query: None
│22:43:37│ ⏳️ sub-01 Writing 232 epochs to disk.
│22:43:37│ ⏳️ sub-01 Adding events plot to report.
│22:43:37│ ⏳️ sub-02 Adding uncleaned epochs to report.
│22:43:37│ ⏳️ sub-03 Created 235 epochs with time interval: -1.0 – 4.0 sec.
│22:43:37│ ⏳️ sub-03 Selected 235 epochs via metadata query: None
│22:43:37│ ⏳️ sub-03 Writing 235 epochs to disk.
│22:43:37│ ⏳️ sub-01 Adding uncleaned epochs to report.
│22:43:37│ ⏳️ sub-03 Adding events plot to report.
│22:43:37│ ⏳️ sub-04 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:43:37│ ⏳️ sub-04 Selected 244 epochs via metadata query: None
│22:43:37│ ⏳️ sub-04 Writing 244 epochs to disk.
│22:43:37│ ⏳️ sub-07 Created 196 epochs with time interval: -1.0 – 4.0 sec.
│22:43:37│ ⏳️ sub-07 Selected 196 epochs via metadata query: None
│22:43:37│ ⏳️ sub-07 Writing 196 epochs to disk.
│22:43:38│ ⏳️ sub-04 Adding events plot to report.
│22:43:38│ ⏳️ sub-07 Adding events plot to report.
│22:43:38│ ⏳️ sub-03 Adding uncleaned epochs to report.
│22:43:38│ ⏳️ sub-04 Adding uncleaned epochs to report.
│22:43:38│ ⏳️ sub-07 Adding uncleaned epochs to report.
│22:43:38│ ⏳️ sub-06 Created 235 epochs with time interval: -1.0 – 4.0 sec.
│22:43:38│ ⏳️ sub-06 Selected 235 epochs via metadata query: None
│22:43:38│ ⏳️ sub-06 Writing 235 epochs to disk.
│22:43:39│ ⏳️ sub-06 Adding events plot to report.
│22:43:39│ ⏳️ sub-02 Adding config and sys info to report
│22:43:39│ ⏳️ sub-01 Adding config and sys info to report
│22:43:39│ ⏳️ sub-06 Adding uncleaned epochs to report.
│22:43:40│ ⏳️ sub-03 Adding config and sys info to report
│22:43:40│ ⏳️ sub-07 Adding config and sys info to report
│22:43:40│ ⏳️ sub-04 Adding config and sys info to report
│22:43:41│ ⏳️ sub-06 Adding config and sys info to report
│22:43:42│ ⏳️ sub-02 Saving report: ]8;id=794498;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=889761;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=880185;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\(]8;;\]8;id=512641;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=880185;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\)]8;;\]8;id=794498;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/]8;;\]8;id=889761;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\sub-02_task-SocialMemoryCuing_report.html]8;;\
│22:43:42│ ⏳️ sub-01 Saving report: ]8;id=972062;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=402652;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=884750;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\(]8;;\]8;id=403267;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=884750;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\)]8;;\]8;id=972062;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/]8;;\]8;id=402652;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\sub-01_task-SocialMemoryCuing_report.html]8;;\
│22:43:42│ ⏳️ sub-03 Saving report: ]8;id=987849;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=677866;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=393789;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\(]8;;\]8;id=552322;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=393789;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\)]8;;\]8;id=987849;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/]8;;\]8;id=677866;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\sub-03_task-SocialMemoryCuing_report.html]8;;\
│22:43:43│ ⏳️ sub-09 Loading filtered raw data from sub-09_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:43│ ⏳️ sub-07 Saving report: ]8;id=904154;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=899859;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=466164;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\(]8;;\]8;id=832818;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=466164;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\)]8;;\]8;id=904154;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/]8;;\]8;id=899859;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\sub-07_task-SocialMemoryCuing_report.html]8;;\
│22:43:43│ ⏳️ sub-10 Loading filtered raw data from sub-10_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:43│ ⏳️ sub-04 Saving report: ]8;id=177843;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=546247;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=7056;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\(]8;;\]8;id=218883;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=7056;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\)]8;;\]8;id=177843;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/]8;;\]8;id=546247;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\sub-04_task-SocialMemoryCuing_report.html]8;;\
│22:43:43│ ⏳️ sub-09 Creating task-related epochs …
│22:43:43│ ⏳️ sub-10 Creating task-related epochs …
│22:43:43│ ⏳️ sub-11 Loading filtered raw data from sub-11_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:43│ ⏳️ sub-12 Loading filtered raw data from sub-12_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:44│ ⏳️ sub-11 Creating task-related epochs …
│22:43:44│ ⏳️ sub-13 Loading filtered raw data from sub-13_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:44│ ⏳️ sub-06 Saving report: ]8;id=332536;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=322201;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=200045;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\(]8;;\]8;id=367833;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=200045;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\)]8;;\]8;id=332536;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/]8;;\]8;id=322201;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\sub-06_task-SocialMemoryCuing_report.html]8;;\
│22:43:44│ ⏳️ sub-12 Creating task-related epochs …
│22:43:44│ ⏳️ sub-13 Creating task-related epochs …
│22:43:45│ ⏳️ sub-14 Loading filtered raw data from sub-14_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:45│ ⏳️ sub-14 Creating task-related epochs …
│22:43:48│ ⏳️ sub-10 Created 240 epochs with time interval: -1.0 – 4.0 sec.
│22:43:48│ ⏳️ sub-10 Selected 240 epochs via metadata query: None
│22:43:48│ ⏳️ sub-09 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:43:48│ ⏳️ sub-10 Writing 240 epochs to disk.
│22:43:48│ ⏳️ sub-09 Selected 244 epochs via metadata query: None
│22:43:48│ ⏳️ sub-09 Writing 244 epochs to disk.
│22:43:48│ ⏳️ sub-10 Adding events plot to report.
│22:43:48│ ⏳️ sub-11 Created 236 epochs with time interval: -1.0 – 4.0 sec.
│22:43:48│ ⏳️ sub-09 Adding events plot to report.
│22:43:48│ ⏳️ sub-11 Selected 236 epochs via metadata query: None
│22:43:48│ ⏳️ sub-11 Writing 236 epochs to disk.
│22:43:48│ ⏳️ sub-11 Adding events plot to report.
│22:43:48│ ⏳️ sub-10 Adding uncleaned epochs to report.
│22:43:48│ ⏳️ sub-09 Adding uncleaned epochs to report.
│22:43:48│ ⏳️ sub-11 Adding uncleaned epochs to report.
│22:43:49│ ⏳️ sub-12 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:43:49│ ⏳️ sub-12 Selected 244 epochs via metadata query: None
│22:43:49│ ⏳️ sub-13 Created 243 epochs with time interval: -1.0 – 4.0 sec.
│22:43:49│ ⏳️ sub-12 Writing 244 epochs to disk.
│22:43:49│ ⏳️ sub-14 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:43:49│ ⏳️ sub-13 Selected 242 epochs via metadata query: None
│22:43:49│ ⏳️ sub-14 Selected 244 epochs via metadata query: None
│22:43:49│ ⏳️ sub-13 Writing 242 epochs to disk.
│22:43:49│ ⏳️ sub-14 Writing 244 epochs to disk.
│22:43:49│ ⏳️ sub-12 Adding events plot to report.
│22:43:49│ ⏳️ sub-14 Adding events plot to report.
│22:43:49│ ⏳️ sub-13 Adding events plot to report.
│22:43:49│ ⏳️ sub-12 Adding uncleaned epochs to report.
│22:43:50│ ⏳️ sub-14 Adding uncleaned epochs to report.
│22:43:50│ ⏳️ sub-13 Adding uncleaned epochs to report.
│22:43:50│ ⏳️ sub-10 Adding config and sys info to report
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│22:43:50│ ⏳️ sub-09 Adding config and sys info to report
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│22:43:50│ ⏳️ sub-11 Adding config and sys info to report
│22:43:50│ ⏳️ sub-11 Saving report: ]8;id=946787;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=80966;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=893124;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\(]8;;\]8;id=840936;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=893124;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\)]8;;\]8;id=946787;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/]8;;\]8;id=80966;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\sub-11_task-SocialMemoryCuing_report.html]8;;\
│22:43:51│ ⏳️ sub-15 Loading filtered raw data from sub-15_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:51│ ⏳️ sub-16 Loading filtered raw data from sub-16_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:51│ ⏳️ sub-17 Loading filtered raw data from sub-17_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:51│ ⏳️ sub-15 Creating task-related epochs …
│22:43:51│ ⏳️ sub-16 Creating task-related epochs …
│22:43:51│ ⏳️ sub-14 Adding config and sys info to report
│22:43:51│ ⏳️ sub-14 Saving report: ]8;id=531993;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=329205;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=323010;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\(]8;;\]8;id=90915;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=323010;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\)]8;;\]8;id=531993;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/]8;;\]8;id=329205;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\sub-14_task-SocialMemoryCuing_report.html]8;;\
│22:43:51│ ⏳️ sub-12 Adding config and sys info to report
│22:43:51│ ⏳️ sub-12 Saving report: ]8;id=84625;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=211928;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=171678;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\(]8;;\]8;id=934601;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=171678;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\)]8;;\]8;id=84625;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/]8;;\]8;id=211928;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\sub-12_task-SocialMemoryCuing_report.html]8;;\
│22:43:51│ ⏳️ sub-17 Creating task-related epochs …
│22:43:51│ ⏳️ sub-13 Adding config and sys info to report
│22:43:51│ ⏳️ sub-13 Saving report: ]8;id=412429;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=442458;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=132883;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\(]8;;\]8;id=571415;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=132883;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\)]8;;\]8;id=412429;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/]8;;\]8;id=442458;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\sub-13_task-SocialMemoryCuing_report.html]8;;\
│22:43:53│ ⏳️ sub-18 Loading filtered raw data from sub-18_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:53│ ⏳️ sub-19 Loading filtered raw data from sub-19_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:53│ ⏳️ sub-21 Loading filtered raw data from sub-21_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:53│ ⏳️ sub-18 Creating task-related epochs …
│22:43:54│ ⏳️ sub-19 Creating task-related epochs …
│22:43:54│ ⏳️ sub-21 Creating task-related epochs …
│22:43:54│ ⏳️ sub-15 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:43:54│ ⏳️ sub-15 Selected 244 epochs via metadata query: None
│22:43:54│ ⏳️ sub-15 Writing 244 epochs to disk.
│22:43:55│ ⏳️ sub-15 Adding events plot to report.
│22:43:55│ ⏳️ sub-16 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:43:55│ ⏳️ sub-16 Selected 244 epochs via metadata query: None
│22:43:55│ ⏳️ sub-16 Writing 244 epochs to disk.
│22:43:55│ ⏳️ sub-16 Adding events plot to report.
│22:43:55│ ⏳️ sub-17 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:43:55│ ⏳️ sub-17 Selected 244 epochs via metadata query: None
│22:43:55│ ⏳️ sub-17 Writing 244 epochs to disk.
│22:43:55│ ⏳️ sub-15 Adding uncleaned epochs to report.
│22:43:55│ ⏳️ sub-17 Adding events plot to report.
│22:43:55│ ⏳️ sub-16 Adding uncleaned epochs to report.
│22:43:55│ ⏳️ sub-17 Adding uncleaned epochs to report.
│22:43:57│ ⏳️ sub-15 Adding config and sys info to report
│22:43:57│ ⏳️ sub-15 Saving report: ]8;id=710595;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=253029;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=235412;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\(]8;;\]8;id=36330;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=235412;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\)]8;;\]8;id=710595;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/]8;;\]8;id=253029;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\sub-15_task-SocialMemoryCuing_report.html]8;;\
│22:43:57│ ⏳️ sub-16 Adding config and sys info to report
│22:43:57│ ⏳️ sub-16 Saving report: ]8;id=883141;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=440481;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=519064;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\(]8;;\]8;id=954238;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=519064;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\)]8;;\]8;id=883141;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/]8;;\]8;id=440481;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\sub-16_task-SocialMemoryCuing_report.html]8;;\
│22:43:57│ ⏳️ sub-17 Adding config and sys info to report
│22:43:57│ ⏳️ sub-17 Saving report: ]8;id=215334;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=277515;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=773343;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\(]8;;\]8;id=619656;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=773343;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\)]8;;\]8;id=215334;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/]8;;\]8;id=277515;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\sub-17_task-SocialMemoryCuing_report.html]8;;\
│22:43:57│ ⏳️ sub-18 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:43:57│ ⏳️ sub-18 Selected 244 epochs via metadata query: None
│22:43:57│ ⏳️ sub-18 Writing 244 epochs to disk.
│22:43:58│ ⏳️ sub-18 Adding events plot to report.
│22:43:58│ ⏳️ sub-19 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:43:58│ ⏳️ sub-19 Selected 244 epochs via metadata query: None
│22:43:58│ ⏳️ sub-19 Writing 244 epochs to disk.
│22:43:58│ ⏳️ sub-22 Loading filtered raw data from sub-22_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:58│ ⏳️ sub-23 Loading filtered raw data from sub-23_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:58│ ⏳️ sub-19 Adding events plot to report.
│22:43:58│ ⏳️ sub-21 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:43:58│ ⏳️ sub-21 Selected 244 epochs via metadata query: None
│22:43:58│ ⏳️ sub-24 Loading filtered raw data from sub-24_task-SocialMemoryCuing_proc-filt_raw.fif
│22:43:58│ ⏳️ sub-21 Writing 244 epochs to disk.
│22:43:58│ ⏳️ sub-21 Adding events plot to report.
│22:43:58│ ⏳️ sub-18 Adding uncleaned epochs to report.
│22:43:58│ ⏳️ sub-19 Adding uncleaned epochs to report.
│22:43:58│ ⏳️ sub-21 Adding uncleaned epochs to report.
│22:43:58│ ⏳️ sub-22 Creating task-related epochs …
│22:43:59│ ⏳️ sub-23 Creating task-related epochs …
│22:43:59│ ⏳️ sub-24 Creating task-related epochs …
│22:44:00│ ⏳️ sub-19 Adding config and sys info to report
│22:44:00│ ⏳️ sub-19 Saving report: ]8;id=970808;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=652001;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=684296;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\(]8;;\]8;id=378041;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=684296;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\)]8;;\]8;id=970808;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/]8;;\]8;id=652001;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\sub-19_task-SocialMemoryCuing_report.html]8;;\
│22:44:00│ ⏳️ sub-18 Adding config and sys info to report
│22:44:00│ ⏳️ sub-18 Saving report: ]8;id=134439;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=588568;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=379618;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\(]8;;\]8;id=2762;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=379618;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\)]8;;\]8;id=134439;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/]8;;\]8;id=588568;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\sub-18_task-SocialMemoryCuing_report.html]8;;\
│22:44:00│ ⏳️ sub-21 Adding config and sys info to report
│22:44:00│ ⏳️ sub-21 Saving report: ]8;id=178655;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=193118;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=320647;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\(]8;;\]8;id=728473;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=320647;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\)]8;;\]8;id=178655;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/]8;;\]8;id=193118;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\sub-21_task-SocialMemoryCuing_report.html]8;;\
│22:44:01│ ⏳️ sub-25 Loading filtered raw data from sub-25_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:01│ ⏳️ sub-27 Loading filtered raw data from sub-27_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:02│ ⏳️ sub-26 Loading filtered raw data from sub-26_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:02│ ⏳️ sub-25 Creating task-related epochs …
│22:44:02│ ⏳️ sub-27 Creating task-related epochs …
│22:44:02│ ⏳️ sub-22 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:44:02│ ⏳️ sub-22 Selected 244 epochs via metadata query: None
│22:44:02│ ⏳️ sub-22 Writing 244 epochs to disk.
│22:44:02│ ⏳️ sub-26 Creating task-related epochs …
│22:44:02│ ⏳️ sub-23 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:44:02│ ⏳️ sub-23 Selected 244 epochs via metadata query: None
│22:44:02│ ⏳️ sub-22 Adding events plot to report.
│22:44:02│ ⏳️ sub-23 Writing 244 epochs to disk.
│22:44:02│ ⏳️ sub-23 Adding events plot to report.
│22:44:02│ ⏳️ sub-24 Created 243 epochs with time interval: -1.0 – 4.0 sec.
│22:44:02│ ⏳️ sub-24 Selected 243 epochs via metadata query: None
│22:44:02│ ⏳️ sub-24 Writing 243 epochs to disk.
│22:44:02│ ⏳️ sub-24 Adding events plot to report.
│22:44:03│ ⏳️ sub-22 Adding uncleaned epochs to report.
│22:44:03│ ⏳️ sub-23 Adding uncleaned epochs to report.
│22:44:03│ ⏳️ sub-24 Adding uncleaned epochs to report.
│22:44:04│ ⏳️ sub-22 Adding config and sys info to report
│22:44:04│ ⏳️ sub-22 Saving report: ]8;id=772028;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=541435;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=162088;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\(]8;;\]8;id=111213;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=162088;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\)]8;;\]8;id=772028;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/]8;;\]8;id=541435;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\sub-22_task-SocialMemoryCuing_report.html]8;;\
│22:44:04│ ⏳️ sub-23 Adding config and sys info to report
│22:44:04│ ⏳️ sub-23 Saving report: ]8;id=979680;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=839483;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=880689;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\(]8;;\]8;id=162444;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=880689;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\)]8;;\]8;id=979680;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/]8;;\]8;id=839483;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\sub-23_task-SocialMemoryCuing_report.html]8;;\
│22:44:04│ ⏳️ sub-24 Adding config and sys info to report
│22:44:04│ ⏳️ sub-24 Saving report: ]8;id=926486;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=473736;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=264144;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\(]8;;\]8;id=830391;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=264144;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\)]8;;\]8;id=926486;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/]8;;\]8;id=473736;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\sub-24_task-SocialMemoryCuing_report.html]8;;\
│22:44:05│ ⏳️ sub-32 Loading filtered raw data from sub-32_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:05│ ⏳️ sub-32 Creating task-related epochs …
│22:44:05│ ⏳️ sub-28 Loading filtered raw data from sub-28_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:05│ ⏳️ sub-30 Loading filtered raw data from sub-30_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:05│ ⏳️ sub-30 Creating task-related epochs …
│22:44:05│ ⏳️ sub-28 Creating task-related epochs …
│22:44:06│ ⏳️ sub-25 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:44:06│ ⏳️ sub-25 Selected 244 epochs via metadata query: None
│22:44:06│ ⏳️ sub-25 Writing 244 epochs to disk.
│22:44:06│ ⏳️ sub-27 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:44:06│ ⏳️ sub-25 Adding events plot to report.
│22:44:06│ ⏳️ sub-27 Selected 244 epochs via metadata query: None
│22:44:06│ ⏳️ sub-27 Writing 244 epochs to disk.
│22:44:06│ ⏳️ sub-27 Adding events plot to report.
│22:44:06│ ⏳️ sub-26 Created 243 epochs with time interval: -1.0 – 4.0 sec.
│22:44:06│ ⏳️ sub-26 Selected 243 epochs via metadata query: None
│22:44:06│ ⏳️ sub-26 Writing 243 epochs to disk.
│22:44:06│ ⏳️ sub-26 Adding events plot to report.
│22:44:06│ ⏳️ sub-25 Adding uncleaned epochs to report.
│22:44:06│ ⏳️ sub-27 Adding uncleaned epochs to report.
│22:44:07│ ⏳️ sub-26 Adding uncleaned epochs to report.
│22:44:08│ ⏳️ sub-25 Adding config and sys info to report
│22:44:08│ ⏳️ sub-25 Saving report: ]8;id=483913;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=100534;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=490396;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\(]8;;\]8;id=394517;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=490396;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\)]8;;\]8;id=483913;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/]8;;\]8;id=100534;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\sub-25_task-SocialMemoryCuing_report.html]8;;\
│22:44:08│ ⏳️ sub-27 Adding config and sys info to report
│22:44:08│ ⏳️ sub-27 Saving report: ]8;id=168783;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=122993;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=12999;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\(]8;;\]8;id=324974;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=12999;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\)]8;;\]8;id=168783;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/]8;;\]8;id=122993;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\sub-27_task-SocialMemoryCuing_report.html]8;;\
│22:44:08│ ⏳️ sub-33 Loading filtered raw data from sub-33_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:08│ ⏳️ sub-34 Loading filtered raw data from sub-34_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:08│ ⏳️ sub-26 Adding config and sys info to report
│22:44:08│ ⏳️ sub-26 Saving report: ]8;id=82218;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=424040;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=526685;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\(]8;;\]8;id=501469;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=526685;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\)]8;;\]8;id=82218;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/]8;;\]8;id=424040;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\sub-26_task-SocialMemoryCuing_report.html]8;;\
│22:44:08│ ⏳️ sub-33 Creating task-related epochs …
│22:44:08│ ⏳️ sub-34 Creating task-related epochs …
│22:44:08│ ⏳️ sub-35 Loading filtered raw data from sub-35_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:09│ ⏳️ sub-35 Creating task-related epochs …
│22:44:09│ ⏳️ sub-32 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:44:09│ ⏳️ sub-32 Selected 244 epochs via metadata query: None
│22:44:09│ ⏳️ sub-32 Writing 244 epochs to disk.
│22:44:09│ ⏳️ sub-32 Adding events plot to report.
│22:44:09│ ⏳️ sub-30 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:44:09│ ⏳️ sub-30 Selected 244 epochs via metadata query: None
│22:44:09│ ⏳️ sub-30 Writing 244 epochs to disk.
│22:44:09│ ⏳️ sub-30 Adding events plot to report.
│22:44:09│ ⏳️ sub-28 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:44:09│ ⏳️ sub-28 Selected 244 epochs via metadata query: None
│22:44:09│ ⏳️ sub-28 Writing 244 epochs to disk.
│22:44:09│ ⏳️ sub-32 Adding uncleaned epochs to report.
│22:44:09│ ⏳️ sub-28 Adding events plot to report.
│22:44:10│ ⏳️ sub-30 Adding uncleaned epochs to report.
│22:44:10│ ⏳️ sub-28 Adding uncleaned epochs to report.
│22:44:11│ ⏳️ sub-32 Adding config and sys info to report
│22:44:11│ ⏳️ sub-32 Saving report: ]8;id=654919;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=620826;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=170811;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\(]8;;\]8;id=164960;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=170811;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\)]8;;\]8;id=654919;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/]8;;\]8;id=620826;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\sub-32_task-SocialMemoryCuing_report.html]8;;\
│22:44:11│ ⏳️ sub-38 Loading filtered raw data from sub-38_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:11│ ⏳️ sub-30 Adding config and sys info to report
│22:44:11│ ⏳️ sub-30 Saving report: ]8;id=870481;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=205357;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=770671;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\(]8;;\]8;id=670944;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=770671;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\)]8;;\]8;id=870481;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/]8;;\]8;id=205357;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\sub-30_task-SocialMemoryCuing_report.html]8;;\
│22:44:12│ ⏳️ sub-38 Creating task-related epochs …
│22:44:12│ ⏳️ sub-28 Adding config and sys info to report
│22:44:12│ ⏳️ sub-28 Saving report: ]8;id=277845;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=139763;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=623297;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\(]8;;\]8;id=981600;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=623297;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\)]8;;\]8;id=277845;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/]8;;\]8;id=139763;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\sub-28_task-SocialMemoryCuing_report.html]8;;\
│22:44:12│ ⏳️ sub-39 Loading filtered raw data from sub-39_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:12│ ⏳️ sub-40 Loading filtered raw data from sub-40_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:12│ ⏳️ sub-39 Creating task-related epochs …
│22:44:12│ ⏳️ sub-40 Creating task-related epochs …
│22:44:12│ ⏳️ sub-33 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:44:12│ ⏳️ sub-33 Selected 244 epochs via metadata query: None
│22:44:12│ ⏳️ sub-33 Writing 244 epochs to disk.
│22:44:12│ ⏳️ sub-35 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:44:12│ ⏳️ sub-35 Selected 244 epochs via metadata query: None
│22:44:12│ ⏳️ sub-35 Writing 244 epochs to disk.
│22:44:12│ ⏳️ sub-33 Adding events plot to report.
│22:44:12│ ⏳️ sub-35 Adding events plot to report.
│22:44:13│ ⏳️ sub-34 Created 239 epochs with time interval: -1.0 – 4.0 sec.
│22:44:13│ ⏳️ sub-34 Selected 239 epochs via metadata query: None
│22:44:13│ ⏳️ sub-34 Writing 239 epochs to disk.
│22:44:13│ ⏳️ sub-34 Adding events plot to report.
│22:44:13│ ⏳️ sub-33 Adding uncleaned epochs to report.
│22:44:13│ ⏳️ sub-35 Adding uncleaned epochs to report.
│22:44:13│ ⏳️ sub-34 Adding uncleaned epochs to report.
│22:44:15│ ⏳️ sub-33 Adding config and sys info to report
│22:44:15│ ⏳️ sub-33 Saving report: ]8;id=866037;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=424071;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=529850;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\(]8;;\]8;id=452499;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=529850;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\)]8;;\]8;id=866037;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/]8;;\]8;id=424071;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\sub-33_task-SocialMemoryCuing_report.html]8;;\
│22:44:15│ ⏳️ sub-41 Loading filtered raw data from sub-41_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:15│ ⏳️ sub-35 Adding config and sys info to report
│22:44:15│ ⏳️ sub-35 Saving report: ]8;id=190481;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=18054;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=766412;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\(]8;;\]8;id=604540;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=766412;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\)]8;;\]8;id=190481;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/]8;;\]8;id=18054;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\sub-35_task-SocialMemoryCuing_report.html]8;;\
│22:44:15│ ⏳️ sub-34 Adding config and sys info to report
│22:44:15│ ⏳️ sub-34 Saving report: ]8;id=871087;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=929242;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=267462;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\(]8;;\]8;id=851034;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=267462;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\)]8;;\]8;id=871087;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/]8;;\]8;id=929242;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\sub-34_task-SocialMemoryCuing_report.html]8;;\
│22:44:15│ ⏳️ sub-43 Loading filtered raw data from sub-43_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:15│ ⏳️ sub-41 Creating task-related epochs …
│22:44:15│ ⏳️ sub-44 Loading filtered raw data from sub-44_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:15│ ⏳️ sub-43 Creating task-related epochs …
│22:44:15│ ⏳️ sub-44 Creating task-related epochs …
│22:44:16│ ⏳️ sub-38 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:44:16│ ⏳️ sub-38 Selected 244 epochs via metadata query: None
│22:44:16│ ⏳️ sub-38 Writing 244 epochs to disk.
│22:44:16│ ⏳️ sub-38 Adding events plot to report.
│22:44:16│ ⏳️ sub-39 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:44:16│ ⏳️ sub-39 Selected 244 epochs via metadata query: None
│22:44:16│ ⏳️ sub-39 Writing 244 epochs to disk.
│22:44:16│ ⏳️ sub-39 Adding events plot to report.
│22:44:16│ ⏳️ sub-40 Created 243 epochs with time interval: -1.0 – 4.0 sec.
│22:44:16│ ⏳️ sub-40 Selected 243 epochs via metadata query: None
│22:44:16│ ⏳️ sub-40 Writing 243 epochs to disk.
│22:44:16│ ⏳️ sub-38 Adding uncleaned epochs to report.
│22:44:16│ ⏳️ sub-40 Adding events plot to report.
│22:44:16│ ⏳️ sub-39 Adding uncleaned epochs to report.
│22:44:17│ ⏳️ sub-40 Adding uncleaned epochs to report.
│22:44:18│ ⏳️ sub-38 Adding config and sys info to report
│22:44:18│ ⏳️ sub-38 Saving report: ]8;id=278020;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=662056;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=618480;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\(]8;;\]8;id=157401;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=618480;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\)]8;;\]8;id=278020;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/]8;;\]8;id=662056;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\sub-38_task-SocialMemoryCuing_report.html]8;;\
│22:44:18│ ⏳️ sub-39 Adding config and sys info to report
│22:44:18│ ⏳️ sub-39 Saving report: ]8;id=397833;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=485223;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=426576;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\(]8;;\]8;id=308896;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=426576;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\)]8;;\]8;id=397833;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/]8;;\]8;id=485223;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\sub-39_task-SocialMemoryCuing_report.html]8;;\
│22:44:18│ ⏳️ sub-45 Loading filtered raw data from sub-45_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:18│ ⏳️ sub-46 Loading filtered raw data from sub-46_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:18│ ⏳️ sub-40 Adding config and sys info to report
│22:44:18│ ⏳️ sub-40 Saving report: ]8;id=842627;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=284964;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=231406;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\(]8;;\]8;id=781276;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=231406;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\)]8;;\]8;id=842627;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/]8;;\]8;id=284964;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\sub-40_task-SocialMemoryCuing_report.html]8;;\
│22:44:18│ ⏳️ sub-45 Creating task-related epochs …
│22:44:19│ ⏳️ sub-48 Loading filtered raw data from sub-48_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:19│ ⏳️ sub-46 Creating task-related epochs …
│22:44:19│ ⏳️ sub-48 Creating task-related epochs …
│22:44:19│ ⏳️ sub-41 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:44:19│ ⏳️ sub-41 Selected 244 epochs via metadata query: None
│22:44:19│ ⏳️ sub-41 Writing 244 epochs to disk.
│22:44:19│ ⏳️ sub-41 Adding events plot to report.
│22:44:19│ ⏳️ sub-44 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:44:19│ ⏳️ sub-44 Selected 244 epochs via metadata query: None
│22:44:19│ ⏳️ sub-44 Writing 244 epochs to disk.
│22:44:19│ ⏳️ sub-43 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:44:19│ ⏳️ sub-43 Selected 244 epochs via metadata query: None
│22:44:20│ ⏳️ sub-43 Writing 244 epochs to disk.
│22:44:20│ ⏳️ sub-41 Adding uncleaned epochs to report.
│22:44:20│ ⏳️ sub-44 Adding events plot to report.
│22:44:20│ ⏳️ sub-43 Adding events plot to report.
│22:44:20│ ⏳️ sub-44 Adding uncleaned epochs to report.
│22:44:20│ ⏳️ sub-43 Adding uncleaned epochs to report.
│22:44:21│ ⏳️ sub-41 Adding config and sys info to report
│22:44:21│ ⏳️ sub-41 Saving report: ]8;id=106914;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=188870;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=116115;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\(]8;;\]8;id=567891;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=116115;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\)]8;;\]8;id=106914;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/]8;;\]8;id=188870;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\sub-41_task-SocialMemoryCuing_report.html]8;;\
│22:44:22│ ⏳️ sub-49 Loading filtered raw data from sub-49_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:22│ ⏳️ sub-44 Adding config and sys info to report
│22:44:22│ ⏳️ sub-44 Saving report: ]8;id=869839;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=858812;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=266467;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\(]8;;\]8;id=281757;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=266467;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\)]8;;\]8;id=869839;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/]8;;\]8;id=858812;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\sub-44_task-SocialMemoryCuing_report.html]8;;\
│22:44:22│ ⏳️ sub-49 Creating task-related epochs …
│22:44:22│ ⏳️ sub-43 Adding config and sys info to report
│22:44:22│ ⏳️ sub-43 Saving report: ]8;id=101859;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=773793;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=527563;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\(]8;;\]8;id=209897;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=527563;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\)]8;;\]8;id=101859;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/]8;;\]8;id=773793;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\sub-43_task-SocialMemoryCuing_report.html]8;;\
│22:44:22│ ⏳️ sub-50 Loading filtered raw data from sub-50_task-SocialMemoryCuing_proc-filt_raw.fif
│22:44:22│ ⏳️ sub-50 Creating task-related epochs …
│22:44:22│ ⏳️ sub-45 Created 243 epochs with time interval: -1.0 – 4.0 sec.
│22:44:22│ ⏳️ sub-45 Selected 243 epochs via metadata query: None
│22:44:22│ ⏳️ sub-45 Writing 243 epochs to disk.
│22:44:23│ ⏳️ sub-45 Adding events plot to report.
│22:44:23│ ⏳️ sub-46 Created 243 epochs with time interval: -1.0 – 4.0 sec.
│22:44:23│ ⏳️ sub-46 Selected 243 epochs via metadata query: None
│22:44:23│ ⏳️ sub-46 Writing 243 epochs to disk.
│22:44:23│ ⏳️ sub-46 Adding events plot to report.
│22:44:23│ ⏳️ sub-48 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:44:23│ ⏳️ sub-48 Selected 244 epochs via metadata query: None
│22:44:23│ ⏳️ sub-48 Writing 244 epochs to disk.
│22:44:23│ ⏳️ sub-48 Adding events plot to report.
│22:44:23│ ⏳️ sub-45 Adding uncleaned epochs to report.
│22:44:23│ ⏳️ sub-46 Adding uncleaned epochs to report.
│22:44:24│ ⏳️ sub-48 Adding uncleaned epochs to report.
│22:44:25│ ⏳️ sub-45 Adding config and sys info to report
│22:44:25│ ⏳️ sub-45 Saving report: ]8;id=984498;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=384271;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=528520;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\(]8;;\]8;id=923137;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=528520;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\)]8;;\]8;id=984498;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/]8;;\]8;id=384271;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\sub-45_task-SocialMemoryCuing_report.html]8;;\
│22:44:25│ ⏳️ sub-46 Adding config and sys info to report
│22:44:25│ ⏳️ sub-46 Saving report: ]8;id=383392;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=798795;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=221939;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\(]8;;\]8;id=188756;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=221939;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\)]8;;\]8;id=383392;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/]8;;\]8;id=798795;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\sub-46_task-SocialMemoryCuing_report.html]8;;\
│22:44:25│ ⏳️ sub-48 Adding config and sys info to report
│22:44:25│ ⏳️ sub-48 Saving report: ]8;id=721566;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=87006;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=580138;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\(]8;;\]8;id=893165;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=580138;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\)]8;;\]8;id=721566;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/]8;;\]8;id=87006;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\sub-48_task-SocialMemoryCuing_report.html]8;;\
│22:44:26│ ⏳️ sub-49 Created 244 epochs with time interval: -1.0 – 4.0 sec.
│22:44:26│ ⏳️ sub-49 Selected 244 epochs via metadata query: None
│22:44:26│ ⏳️ sub-49 Writing 244 epochs to disk.
│22:44:26│ ⏳️ sub-49 Adding events plot to report.
│22:44:26│ ⏳️ sub-49 Adding uncleaned epochs to report.
│22:44:26│ ⏳️ sub-50 Created 243 epochs with time interval: -1.0 – 4.0 sec.
│22:44:26│ ⏳️ sub-50 Selected 243 epochs via metadata query: None
│22:44:26│ ⏳️ sub-50 Writing 243 epochs to disk.
│22:44:26│ ⏳️ sub-50 Adding events plot to report.
│22:44:27│ ⏳️ sub-50 Adding uncleaned epochs to report.
│22:44:28│ ⏳️ sub-49 Adding config and sys info to report
│22:44:28│ ⏳️ sub-49 Saving report: ]8;id=824442;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=690273;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=937678;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\(]8;;\]8;id=56363;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=937678;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\)]8;;\]8;id=824442;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/]8;;\]8;id=690273;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\sub-49_task-SocialMemoryCuing_report.html]8;;\
│22:44:28│ ⏳️ sub-50 Adding config and sys info to report
│22:44:28│ ⏳️ sub-50 Saving report: ]8;id=518857;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=353110;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=436099;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\(]8;;\]8;id=68950;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=436099;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\)]8;;\]8;id=518857;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/]8;;\]8;id=353110;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\sub-50_task-SocialMemoryCuing_report.html]8;;\
└────────┴ done (57s)
In [69]:
# checkup: plot epochs
curr_checkup_epochs = mne.read_epochs(f"{curr_subject_path}/sub-01_task-SocialMemoryCuing_epo.fif")
mne.viz.plot_epochs_image(curr_checkup_epochs)
No description has been provided for this image
Out[69]:
[<Figure size 640x480 with 3 Axes>]

This checkup plot shows the amplitude in μV per epoch over time. Here, increased activity is visible around -1 seconds, and at 0.5 to 3 seconds. The roughly matching onset time of the activity and time frames with low amplitudes indicate a roughly correct epoching.

Next, we compare the detected number of epochs with the expected number of epochs recovered from the provided metadata.

In [26]:
# checkup: print lost epochs
import pandas
from mne.epochs import EpochsFIF

FILE_PATH_TEMPLATE = '{data}/derivatives/mne-bids-pipeline/sub-{sub}/eeg/sub-{sub}_task-SocialMemoryCuing_epo.fif'

METADATA_PATH_TEMPLATE = '{data}/derivatives/BehaviouralData_TableStudyVR/TableStudyRawdata/sub-{sub}/sub-{sub}__task-SocialMemoryCuing_{cue}_trial_results.csv'

SUBJECT_IDS = [ "01", "02", "03", "04",       "06", "07",       "09", "10",
                "11", "12", "13", "14", "15", "16", "17", "18", "19",
                "21", "22", "23", "24", "25", "26", "27", "28",       "30",
                "32", "33", "34", "35",             "38", "39", "40",
                "41",       "43", "44", "45", "46",       "48", "49", "50"]

CLEAN_SUBJECT_IDS = []

clean_subjects = 0

for sub_str in SUBJECT_IDS:
    path = FILE_PATH_TEMPLATE.format(data=cfg.bids_root, sub=sub_str)
    epochs: EpochsFIF = mne.read_epochs(path)

    detected_stick_length = len(epochs['sticks'].metadata)
    detected_avatar_length = len(epochs['avatar'].metadata)

    path_meta_avatar = METADATA_PATH_TEMPLATE.format(data=cfg.bids_root, sub=sub_str, cue="AVATAR")
    path_meta_stick = METADATA_PATH_TEMPLATE.format(data=cfg.bids_root, sub=sub_str, cue="STICK")

    meta_avatar_length = len(pandas.read_csv(path_meta_avatar))
    meta_stick_length = len(pandas.read_csv(path_meta_stick))
    
    isClean = False
    
    if meta_avatar_length - detected_avatar_length == 0 and meta_stick_length - detected_stick_length == 0:
        clean_subjects += 1
        CLEAN_SUBJECT_IDS.append(sub_str)
        isClean = True
    log.print("Subject {}: Lost Epochs: Avatar: {} Sticks: {}".format(sub_str,
                                                                  meta_avatar_length - detected_avatar_length,
                                                                  meta_stick_length - detected_stick_length), style=log.STYLE_TEXT_GREEN if isClean else log.STYLE_HIGHLIGHT_RED)

log.print(log.formatString("Total number of Subjects without missing Epochs:", style=log.STYLE_TEXT_BLUE), log.formatString(clean_subjects, style=[log.STYLE_BOLD, log.STYLE_TEXT_DARK_YELLOW]))

log.print(log.formatString("The following subjects are clean:", style=log.STYLE_TEXT_BLUE), log.formatString(*CLEAN_SUBJECT_IDS, style=log.STYLE_TEXT_DARK_YELLOW, sep=', '))

Subject 01: Lost Epochs: Avatar: 0 Sticks: 3
Subject 02: Lost Epochs: Avatar: 0 Sticks: 28
Subject 03: Lost Epochs: Avatar: 0 Sticks: 0
Subject 04: Lost Epochs: Avatar: 0 Sticks: 0
Subject 06: Lost Epochs: Avatar: 0 Sticks: 0
Subject 07: Lost Epochs: Avatar: 48 Sticks: 0
Subject 09: Lost Epochs: Avatar: 0 Sticks: 0
Subject 10: Lost Epochs: Avatar: 4 Sticks: 0
Subject 11: Lost Epochs: Avatar: 0 Sticks: 0
Subject 12: Lost Epochs: Avatar: 0 Sticks: 0
Subject 13: Lost Epochs: Avatar: 0 Sticks: 2
Subject 14: Lost Epochs: Avatar: 0 Sticks: 0
Subject 15: Lost Epochs: Avatar: 0 Sticks: 0
Subject 16: Lost Epochs: Avatar: 0 Sticks: 0
Subject 17: Lost Epochs: Avatar: 0 Sticks: 0
Subject 18: Lost Epochs: Avatar: 0 Sticks: 0
Subject 19: Lost Epochs: Avatar: 0 Sticks: 0
Subject 21: Lost Epochs: Avatar: 0 Sticks: 0
Subject 22: Lost Epochs: Avatar: 0 Sticks: 0
Subject 23: Lost Epochs: Avatar: 0 Sticks: 0
Subject 24: Lost Epochs: Avatar: 1 Sticks: 0
Subject 25: Lost Epochs: Avatar: 0 Sticks: 0
Subject 26: Lost Epochs: Avatar: 1 Sticks: 0
Subject 27: Lost Epochs: Avatar: 0 Sticks: 0
Subject 28: Lost Epochs: Avatar: 0 Sticks: 0
Subject 30: Lost Epochs: Avatar: 0 Sticks: 0
Subject 32: Lost Epochs: Avatar: 0 Sticks: 0
Subject 33: Lost Epochs: Avatar: 0 Sticks: 0
Subject 34: Lost Epochs: Avatar: 5 Sticks: 0
Subject 35: Lost Epochs: Avatar: 0 Sticks: 0
Subject 38: Lost Epochs: Avatar: 0 Sticks: 0
Subject 39: Lost Epochs: Avatar: 0 Sticks: 0
Subject 40: Lost Epochs: Avatar: 1 Sticks: 0
Subject 41: Lost Epochs: Avatar: 0 Sticks: 0
Subject 43: Lost Epochs: Avatar: 0 Sticks: 0
Subject 44: Lost Epochs: Avatar: 0 Sticks: 0
Subject 45: Lost Epochs: Avatar: 0 Sticks: 1
Subject 46: Lost Epochs: Avatar: 1 Sticks: 0
Subject 48: Lost Epochs: Avatar: 0 Sticks: 0
Subject 49: Lost Epochs: Avatar: 0 Sticks: 0
Subject 50: Lost Epochs: Avatar: 1 Sticks: 0
Total number of Subjects without missing Epochs: 29
The following subjects are clean: 03, 04, 06, 09, 11, 12, 14, 15, 16, 17, 18, 19, 21, 22, 23, 25, 27, 28, 30, 32, 33, 35, 38, 39, 41, 43, 44, 48, 49

As we can see, this results in only 29 subjects without any lost epochs. Lost epochs can be problematic when applying the external metadata, since the locations of the lost epochs are not known, which may leads to misalignment between measured data and metadata. Unfortunately, mne-bids-pipeline does not seem to store the original timecodes of epochs in the metadata. Therefore, we can not match detected epochs with external metadata by timecode.

If more subjects are needed, matching epochs by their measurement values (or their deltas) would be possible. Given the 500 floating point samples per epoch (because of subsampling to 100 hz and an epoch length of 5 seconds), this should provide a reasonably good chance to identify the epochs. Due to the limited scope of this project, and 29 subjects still being enough for the purpose of this course, we decided not to implement this rather convoluted, computationally expensive epoch identification method.

Pre-processing: Add Additional Metadata¶

In [27]:
from pandas import DataFrame
import pandas as pd

for sub_str in CLEAN_SUBJECT_IDS:
    path = FILE_PATH_TEMPLATE.format(data=cfg.bids_root, sub=sub_str)
    epochs: EpochsFIF = mne.read_epochs(path)

    detected_avatar_length = len(epochs['avatar'].metadata)
    

    path_meta_avatar = METADATA_PATH_TEMPLATE.format(data=cfg.bids_root, sub=sub_str, cue="AVATAR")
    path_meta_stick = METADATA_PATH_TEMPLATE.format(data=cfg.bids_root, sub=sub_str, cue="STICK")
    
    avatar_extern = pandas.read_csv(path_meta_avatar, index_col=False)
    stick_extern = pandas.read_csv(path_meta_stick, index_col=False)
    
    avatar_intern: DataFrame = epochs['avatar'].metadata
    stick_intern = epochs['sticks'].metadata
    
    idx_avatar = avatar_intern.index[0]
    idx_sticks = stick_intern.index[0]
    
    if idx_avatar < idx_sticks:
        extern = pd.concat([avatar_extern, stick_extern], axis=0, ignore_index=True)
    else:
        extern = pd.concat([stick_extern, avatar_extern], axis=0, ignore_index=True)
    
    metadata = pd.concat([epochs.metadata, extern], axis=1)
    
    epochs.metadata = metadata
    epochs.save(path, overwrite=True)

With this, we add the additional metadata provided for the study, and save the epochs with additional metadata for further processing using the pipeline. In order to verify that adding the metadata worked properly, we take a quick look at the saved epoch's metadata for subject 3.

In [28]:
from IPython.display import display

path = FILE_PATH_TEMPLATE.format(data=cfg.bids_root, sub="03")
epochs: EpochsFIF = mne.read_epochs(path)

frame: DataFrame = epochs.metadata
display(frame)
event_name Impedance avatar s3001 s3002 s3003 s3004 s3005 s3006 ... Gaze ItemSide SameLoc Case PersonShown ProbeObject ResponseTimeLocation ResponseTimeStatus QuestionAsked ConditionNumber
0 sticks None None NaN None None None None None None ... Left Right Yes None None ProbePlate(Clone) 1.242018 1.299345 Was the bowl empty? 4
1 sticks None None NaN None None None None None None ... Left Right Yes None None ProbeTeacup(Clone) 1.303890 1.488068 Was the bowl empty? 4
2 sticks None None NaN None None None None None None ... Left Left No None None ProbeTeacup(Clone) 2.125694 2.437103 Was the teapot cracked? 1
3 sticks None None NaN None None None None None None ... Left Left No None None ProbeTeacup(Clone) 1.163239 2.412155 Was the teapot free from cracks? 1
4 sticks None None NaN None None None None None None ... Right Left No None None ProbeTeacup(Clone) 1.750244 2.322540 Did the croissant have a bite in it? 7
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
230 avatar None None 0.0 None None None None None None ... Left Left No None MC04PrefabLeft ProbeTeacup(Clone) 1.024780 0.936890 Did the cup have coffee in it? 1
231 avatar None None 0.0 None None None None None None ... Left Right Yes None MC04PrefabLeft ProbeTeapot(Clone) 1.074585 1.112305 Was the coffee cup empty? 4
232 avatar None None 0.0 None None None None None None ... Right Left Yes None FC01PrefabRight ProbeTeapot(Clone) 0.675537 1.811279 Did the cup have coffee in it? 6
233 avatar None None 0.0 None None None None None None ... Left Left No None MC04PrefabLeft ProbeTeacup(Clone) 0.975098 1.274414 Was the teapot cracked? 1
234 avatar None None 0.0 None None None None None None ... Right Right No None MC04PrefabRight ProbeTeacup(Clone) 1.649902 0.962769 Was the bowl empty? 3

235 rows × 52 columns

This checkup output contains additional columns for meta data like the asked question. These were added by the current step in the pipeline.

Pre-processing: ICA¶

Running the ICA is split to three steps:

  • component analysis
  • component labelling (good vs. bad)
  • signal cleaning

ICA: Analysis¶

For the analysis, per subject the algorithm selected in the configuration file gets run. Here, extended infomax is selected, which follows peak to peak rejection (PTP) for better ICA results. Since with low threshold the PTP does not return enough epochs, a high threshold of 400 μV is selected matching the default pipeline threshold.

For few subjects, the amplitudes are too high for this PTP threshold. Here, two possibilities seem to be reachable: Either few subjects need to get removed from the pipeline due to too high amplitudes resulting in removal of all epochs, or the threshold needs to get increased to a value above all subjects amplitude. To reach a good overall quality, the subjects 5, 20, and 29 are removed from the pipeline.

More accurate PTP is later run on the ICA cleaned epoch signals.

The analysis is followed by a checkup plot of unlabelled components.

In [29]:
curr_steps = "preprocessing/_06a_run_ica"
if curr_steps in STEPS_TO_RUN and STEPS_TO_RUN[curr_steps]:
    !mne_bids_pipeline --config {config_path} --steps {curr_steps}

┌────────┬ Welcome aboard MNE-BIDS-Pipeline! 👋 ────────────────────────────────
│22:44:49│ 📝 Using configuration: ./mne-bids/config/mne-bids-pipeline.py
└────────┴ 
┌────────┬ init/_01_init_derivatives_dir ───────────────────────────────────────
│22:44:49│ ✅ Output directories already exist …
└────────┴ done (1s)
┌────────┬ init/_02_find_empty_room ────────────────────────────────────────────
│22:44:49│ ⏩ Skipping, empty-room data only relevant for MEG …
└────────┴ done (1s)
┌────────┬ preprocessing/_06a_run_ica ──────────────────────────────────────────
│22:44:50│ ⏳️ sub-02 Loading filtered raw data from sub-02_task-SocialMemoryCuing_proc-filt_raw
│22:44:50│ ⏳️ sub-01 Loading filtered raw data from sub-01_task-SocialMemoryCuing_proc-filt_raw
│22:44:50│ ⏳️ sub-03 Loading filtered raw data from sub-03_task-SocialMemoryCuing_proc-filt_raw
│22:44:50│ ⏳️ sub-06 Loading filtered raw data from sub-06_task-SocialMemoryCuing_proc-filt_raw
│22:44:50│ ⏳️ sub-02 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:44:50│ ⏳️ sub-01 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:44:50│ ⏳️ sub-03 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:44:50│ ⏳️ sub-06 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:44:50│ ⏳️ sub-04 Loading filtered raw data from sub-04_task-SocialMemoryCuing_proc-filt_raw
│22:44:50│ ⏳️ sub-07 Loading filtered raw data from sub-07_task-SocialMemoryCuing_proc-filt_raw
│22:44:50│ ⏳️ sub-04 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:44:51│ ⏳️ sub-07 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:44:51│ ⏳️ sub-02 No EOG channel is present. Cannot automate IC detection for EOG
│22:44:51│ ⏳️ sub-02 Applying high-pass filter with 1.0 Hz cutoff …
│22:44:51│ ⏳️ sub-01 No EOG channel is present. Cannot automate IC detection for EOG
│22:44:51│ ⏳️ sub-01 Applying high-pass filter with 1.0 Hz cutoff …
│22:44:51│ ⏳️ sub-06 No EOG channel is present. Cannot automate IC detection for EOG
│22:44:51│ ⏳️ sub-06 Applying high-pass filter with 1.0 Hz cutoff …
│22:44:51│ ⏳️ sub-03 No EOG channel is present. Cannot automate IC detection for EOG
│22:44:51│ ⏳️ sub-03 Applying high-pass filter with 1.0 Hz cutoff …
│22:44:51│ ⏳️ sub-07 No EOG channel is present. Cannot automate IC detection for EOG
│22:44:51│ ⏳️ sub-07 Applying high-pass filter with 1.0 Hz cutoff …
│22:44:51│ ⏳️ sub-04 No EOG channel is present. Cannot automate IC detection for EOG
│22:44:51│ ⏳️ sub-04 Applying high-pass filter with 1.0 Hz cutoff …
│22:44:51│ ⏳️ sub-01 Creating task-related epochs …
│22:44:51│ ⏳️ sub-02 Creating task-related epochs …
│22:44:51│ ⏳️ sub-06 Creating task-related epochs …
│22:44:51│ ⏳️ sub-04 Creating task-related epochs …
│22:44:51│ ⏳️ sub-07 Creating task-related epochs …
│22:44:52│ ⏳️ sub-03 Creating task-related epochs …
│22:44:54│ ⏳️ sub-02 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:44:54│ ⏳️ sub-02 Calculating ICA solution using method: extended_infomax.
│22:44:55│ ⏳️ sub-01 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:44:55│ ⏳️ sub-01 Calculating ICA solution using method: extended_infomax.
│22:44:55│ ⏳️ sub-03 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:44:55│ ⏳️ sub-03 Calculating ICA solution using method: extended_infomax.
│22:44:55│ ⏳️ sub-04 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:44:55│ ⏳️ sub-04 Calculating ICA solution using method: extended_infomax.
│22:44:56│ ⏳️ sub-07 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:44:56│ ⏳️ sub-07 Calculating ICA solution using method: extended_infomax.
│22:44:57│ ⏳️ sub-06 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:44:58│ ⏳️ sub-06 Calculating ICA solution using method: extended_infomax.
│22:45:02│ ⏳️ sub-07 Fit 8 components (explaining 95.4% of the variance) in 3000 iterations.
│22:45:02│ ⏳️ sub-07 Saving ICA solution and detected artifacts to disk.
│22:45:02│ ⏳️ sub-07 Adding diagnostic plots for all ICA components to the HTML report …
│22:45:08│ ⏳️ sub-04 Fit 7 components (explaining 95.3% of the variance) in 3000 iterations.
│22:45:08│ ⏳️ sub-04 Saving ICA solution and detected artifacts to disk.
│22:45:08│ ⏳️ sub-04 Adding diagnostic plots for all ICA components to the HTML report …
│22:45:12│ ⏳️ sub-07 ICA completed. Please carefully review the extracted ICs in the report sub-07_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-07_task-SocialMemoryCuing_proc-ica_components.tsv
│22:45:12│ ⏳️ sub-09 Loading filtered raw data from sub-09_task-SocialMemoryCuing_proc-filt_raw
│22:45:12│ ⏳️ sub-09 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:45:12│ ⏳️ sub-09 No EOG channel is present. Cannot automate IC detection for EOG
│22:45:12│ ⏳️ sub-09 Applying high-pass filter with 1.0 Hz cutoff …
│22:45:13│ ⏳️ sub-09 Creating task-related epochs …
│22:45:14│ ⏳️ sub-03 Fit 15 components (explaining 95.2% of the variance) in 3000 iterations.
│22:45:14│ ⏳️ sub-03 Saving ICA solution and detected artifacts to disk.
│22:45:14│ ⏳️ sub-03 Adding diagnostic plots for all ICA components to the HTML report …
│22:45:14│ ⏳️ sub-01 Fit 14 components (explaining 95.0% of the variance) in 3000 iterations.
│22:45:14│ ⏳️ sub-01 Saving ICA solution and detected artifacts to disk.
│22:45:14│ ⏳️ sub-01 Adding diagnostic plots for all ICA components to the HTML report …
│22:45:18│ ⏳️ sub-09 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:45:18│ ⏳️ sub-09 Calculating ICA solution using method: extended_infomax.
│22:45:20│ ⏳️ sub-04 ICA completed. Please carefully review the extracted ICs in the report sub-04_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-04_task-SocialMemoryCuing_proc-ica_components.tsv
│22:45:20│ ⏳️ sub-10 Loading filtered raw data from sub-10_task-SocialMemoryCuing_proc-filt_raw
│22:45:20│ ⏳️ sub-02 Fit 23 components (explaining 95.2% of the variance) in 3000 iterations.
│22:45:20│ ⏳️ sub-02 Saving ICA solution and detected artifacts to disk.
│22:45:20│ ⏳️ sub-02 Adding diagnostic plots for all ICA components to the HTML report …
│22:45:20│ ⏳️ sub-10 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:45:20│ ⏳️ sub-10 No EOG channel is present. Cannot automate IC detection for EOG
│22:45:20│ ⏳️ sub-10 Applying high-pass filter with 1.0 Hz cutoff …
│22:45:21│ ⏳️ sub-10 Creating task-related epochs …
│22:45:22│ ⏳️ sub-06 Fit 20 components (explaining 95.2% of the variance) in 3000 iterations.
│22:45:22│ ⏳️ sub-06 Saving ICA solution and detected artifacts to disk.
│22:45:22│ ⏳️ sub-06 Adding diagnostic plots for all ICA components to the HTML report …
│22:45:25│ ⏳️ sub-10 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:45:25│ ⏳️ sub-10 Calculating ICA solution using method: extended_infomax.
│22:45:30│ ⏳️ sub-09 Fit 7 components (explaining 95.2% of the variance) in 3000 iterations.
│22:45:30│ ⏳️ sub-09 Saving ICA solution and detected artifacts to disk.
│22:45:30│ ⏳️ sub-09 Adding diagnostic plots for all ICA components to the HTML report …
│22:45:33│ ⏳️ sub-01 ICA completed. Please carefully review the extracted ICs in the report sub-01_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-01_task-SocialMemoryCuing_proc-ica_components.tsv
│22:45:33│ ⏳️ sub-11 Loading filtered raw data from sub-11_task-SocialMemoryCuing_proc-filt_raw
│22:45:33│ ⏳️ sub-11 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:45:33│ ⏳️ sub-03 ICA completed. Please carefully review the extracted ICs in the report sub-03_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-03_task-SocialMemoryCuing_proc-ica_components.tsv
│22:45:33│ ⏳️ sub-11 No EOG channel is present. Cannot automate IC detection for EOG
│22:45:33│ ⏳️ sub-11 Applying high-pass filter with 1.0 Hz cutoff …
│22:45:33│ ⏳️ sub-12 Loading filtered raw data from sub-12_task-SocialMemoryCuing_proc-filt_raw
│22:45:34│ ⏳️ sub-12 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:45:34│ ⏳️ sub-12 No EOG channel is present. Cannot automate IC detection for EOG
│22:45:34│ ⏳️ sub-12 Applying high-pass filter with 1.0 Hz cutoff …
│22:45:34│ ⏳️ sub-11 Creating task-related epochs …
│22:45:34│ ⏳️ sub-12 Creating task-related epochs …
│22:45:37│ ⏳️ sub-10 Fit 8 components (explaining 95.2% of the variance) in 3000 iterations.
│22:45:37│ ⏳️ sub-10 Saving ICA solution and detected artifacts to disk.
│22:45:37│ ⏳️ sub-10 Adding diagnostic plots for all ICA components to the HTML report …
│22:45:39│ ⏳️ sub-11 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:45:39│ ⏳️ sub-11 Calculating ICA solution using method: extended_infomax.
│22:45:40│ ⏳️ sub-12 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:45:40│ ⏳️ sub-12 Calculating ICA solution using method: extended_infomax.
│22:45:43│ ⏳️ sub-09 ICA completed. Please carefully review the extracted ICs in the report sub-09_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-09_task-SocialMemoryCuing_proc-ica_components.tsv
│22:45:43│ ⏳️ sub-13 Loading filtered raw data from sub-13_task-SocialMemoryCuing_proc-filt_raw
│22:45:43│ ⏳️ sub-13 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:45:43│ ⏳️ sub-13 No EOG channel is present. Cannot automate IC detection for EOG
│22:45:43│ ⏳️ sub-13 Applying high-pass filter with 1.0 Hz cutoff …
│22:45:44│ ⏳️ sub-13 Creating task-related epochs …
│22:45:47│ ⏳️ sub-11 Fit 9 components (explaining 95.3% of the variance) in 3000 iterations.
│22:45:47│ ⏳️ sub-11 Saving ICA solution and detected artifacts to disk.
│22:45:47│ ⏳️ sub-11 Adding diagnostic plots for all ICA components to the HTML report …
│22:45:47│ ⏳️ sub-02 ICA completed. Please carefully review the extracted ICs in the report sub-02_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-02_task-SocialMemoryCuing_proc-ica_components.tsv
│22:45:47│ ⏳️ sub-14 Loading filtered raw data from sub-14_task-SocialMemoryCuing_proc-filt_raw
│22:45:47│ ⏳️ sub-14 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:45:48│ ⏳️ sub-14 No EOG channel is present. Cannot automate IC detection for EOG
│22:45:48│ ⏳️ sub-14 Applying high-pass filter with 1.0 Hz cutoff …
│22:45:48│ ⏳️ sub-06 ICA completed. Please carefully review the extracted ICs in the report sub-06_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-06_task-SocialMemoryCuing_proc-ica_components.tsv
│22:45:48│ ⏳️ sub-15 Loading filtered raw data from sub-15_task-SocialMemoryCuing_proc-filt_raw
│22:45:48│ ⏳️ sub-15 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:45:48│ ⏳️ sub-14 Creating task-related epochs …
│22:45:48│ ⏳️ sub-15 No EOG channel is present. Cannot automate IC detection for EOG
│22:45:48│ ⏳️ sub-15 Applying high-pass filter with 1.0 Hz cutoff …
│22:45:48│ ⏳️ sub-13 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:45:48│ ⏳️ sub-13 Calculating ICA solution using method: extended_infomax.
│22:45:49│ ⏳️ sub-15 Creating task-related epochs …
│22:45:50│ ⏳️ sub-10 ICA completed. Please carefully review the extracted ICs in the report sub-10_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-10_task-SocialMemoryCuing_proc-ica_components.tsv
│22:45:50│ ⏳️ sub-16 Loading filtered raw data from sub-16_task-SocialMemoryCuing_proc-filt_raw
│22:45:50│ ⏳️ sub-16 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:45:50│ ⏳️ sub-16 No EOG channel is present. Cannot automate IC detection for EOG
│22:45:50│ ⏳️ sub-16 Applying high-pass filter with 1.0 Hz cutoff …
│22:45:51│ ⏳️ sub-16 Creating task-related epochs …
│22:45:52│ ⏳️ sub-14 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:45:52│ ⏳️ sub-14 Calculating ICA solution using method: extended_infomax.
│22:45:53│ ⏳️ sub-15 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:45:53│ ⏳️ sub-15 Calculating ICA solution using method: extended_infomax.
│22:45:55│ ⏳️ sub-16 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:45:55│ ⏳️ sub-16 Calculating ICA solution using method: extended_infomax.
│22:45:58│ ⏳️ sub-12 Fit 13 components (explaining 95.5% of the variance) in 3000 iterations.
│22:45:58│ ⏳️ sub-12 Saving ICA solution and detected artifacts to disk.
│22:45:58│ ⏳️ sub-12 Adding diagnostic plots for all ICA components to the HTML report …
│22:45:59│ ⏳️ sub-11 ICA completed. Please carefully review the extracted ICs in the report sub-11_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-11_task-SocialMemoryCuing_proc-ica_components.tsv
│22:45:59│ ⏳️ sub-17 Loading filtered raw data from sub-17_task-SocialMemoryCuing_proc-filt_raw
│22:45:59│ ⏳️ sub-17 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:45:59│ ⏳️ sub-17 No EOG channel is present. Cannot automate IC detection for EOG
│22:45:59│ ⏳️ sub-17 Applying high-pass filter with 1.0 Hz cutoff …
│22:46:00│ ⏳️ sub-17 Creating task-related epochs …
│22:46:03│ ⏳️ sub-17 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:46:03│ ⏳️ sub-17 Calculating ICA solution using method: extended_infomax.
│22:46:04│ ⏳️ sub-14 Fit 7 components (explaining 95.0% of the variance) in 3000 iterations.
│22:46:04│ ⏳️ sub-14 Saving ICA solution and detected artifacts to disk.
│22:46:04│ ⏳️ sub-14 Adding diagnostic plots for all ICA components to the HTML report …
│22:46:06│ ⏳️ sub-16 Fit 7 components (explaining 95.6% of the variance) in 3000 iterations.
│22:46:06│ ⏳️ sub-16 Saving ICA solution and detected artifacts to disk.
│22:46:06│ ⏳️ sub-16 Adding diagnostic plots for all ICA components to the HTML report …
│22:46:09│ ⏳️ sub-13 Fit 15 components (explaining 95.3% of the variance) in 3000 iterations.
│22:46:09│ ⏳️ sub-13 Saving ICA solution and detected artifacts to disk.
│22:46:09│ ⏳️ sub-13 Adding diagnostic plots for all ICA components to the HTML report …
│22:46:11│ ⏳️ sub-15 Fit 14 components (explaining 95.2% of the variance) in 3000 iterations.
│22:46:11│ ⏳️ sub-15 Saving ICA solution and detected artifacts to disk.
│22:46:11│ ⏳️ sub-15 Adding diagnostic plots for all ICA components to the HTML report …
│22:46:16│ ⏳️ sub-12 ICA completed. Please carefully review the extracted ICs in the report sub-12_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-12_task-SocialMemoryCuing_proc-ica_components.tsv
│22:46:16│ ⏳️ sub-18 Loading filtered raw data from sub-18_task-SocialMemoryCuing_proc-filt_raw
│22:46:16│ ⏳️ sub-18 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:46:17│ ⏳️ sub-14 ICA completed. Please carefully review the extracted ICs in the report sub-14_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-14_task-SocialMemoryCuing_proc-ica_components.tsv
│22:46:17│ ⏳️ sub-18 No EOG channel is present. Cannot automate IC detection for EOG
│22:46:17│ ⏳️ sub-18 Applying high-pass filter with 1.0 Hz cutoff …
│22:46:17│ ⏳️ sub-19 Loading filtered raw data from sub-19_task-SocialMemoryCuing_proc-filt_raw
│22:46:17│ ⏳️ sub-19 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:46:17│ ⏳️ sub-19 No EOG channel is present. Cannot automate IC detection for EOG
│22:46:17│ ⏳️ sub-19 Applying high-pass filter with 1.0 Hz cutoff …
│22:46:17│ ⏳️ sub-18 Creating task-related epochs …
│22:46:18│ ⏳️ sub-19 Creating task-related epochs …
│22:46:20│ ⏳️ sub-16 ICA completed. Please carefully review the extracted ICs in the report sub-16_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-16_task-SocialMemoryCuing_proc-ica_components.tsv
│22:46:20│ ⏳️ sub-21 Loading filtered raw data from sub-21_task-SocialMemoryCuing_proc-filt_raw
│22:46:20│ ⏳️ sub-21 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:46:20│ ⏳️ sub-21 No EOG channel is present. Cannot automate IC detection for EOG
│22:46:20│ ⏳️ sub-21 Applying high-pass filter with 1.0 Hz cutoff …
│22:46:21│ ⏳️ sub-21 Creating task-related epochs …
│22:46:21│ ⏳️ sub-17 Fit 13 components (explaining 95.3% of the variance) in 3000 iterations.
│22:46:21│ ⏳️ sub-17 Saving ICA solution and detected artifacts to disk.
│22:46:21│ ⏳️ sub-17 Adding diagnostic plots for all ICA components to the HTML report …
│22:46:21│ ⏳️ sub-18 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:46:21│ ⏳️ sub-18 Calculating ICA solution using method: extended_infomax.
│22:46:22│ ⏳️ sub-19 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:46:22│ ⏳️ sub-19 Calculating ICA solution using method: extended_infomax.
│22:46:25│ ⏳️ sub-21 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:46:25│ ⏳️ sub-21 Calculating ICA solution using method: extended_infomax.
│22:46:30│ ⏳️ sub-13 ICA completed. Please carefully review the extracted ICs in the report sub-13_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-13_task-SocialMemoryCuing_proc-ica_components.tsv
│22:46:30│ ⏳️ sub-22 Loading filtered raw data from sub-22_task-SocialMemoryCuing_proc-filt_raw
│22:46:30│ ⏳️ sub-15 ICA completed. Please carefully review the extracted ICs in the report sub-15_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-15_task-SocialMemoryCuing_proc-ica_components.tsv
│22:46:30│ ⏳️ sub-23 Loading filtered raw data from sub-23_task-SocialMemoryCuing_proc-filt_raw
│22:46:30│ ⏳️ sub-22 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:46:30│ ⏳️ sub-23 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:46:31│ ⏳️ sub-22 No EOG channel is present. Cannot automate IC detection for EOG
│22:46:31│ ⏳️ sub-22 Applying high-pass filter with 1.0 Hz cutoff …
│22:46:31│ ⏳️ sub-23 No EOG channel is present. Cannot automate IC detection for EOG
│22:46:31│ ⏳️ sub-23 Applying high-pass filter with 1.0 Hz cutoff …
│22:46:31│ ⏳️ sub-22 Creating task-related epochs …
│22:46:31│ ⏳️ sub-23 Creating task-related epochs …
│22:46:32│ ⏳️ sub-21 Fit 5 components (explaining 95.1% of the variance) in 3000 iterations.
│22:46:33│ ⏳️ sub-21 Saving ICA solution and detected artifacts to disk.
│22:46:33│ ⏳️ sub-21 Adding diagnostic plots for all ICA components to the HTML report …
│22:46:34│ ⏳️ sub-18 Fit 7 components (explaining 95.3% of the variance) in 3000 iterations.
│22:46:34│ ⏳️ sub-18 Saving ICA solution and detected artifacts to disk.
│22:46:34│ ⏳️ sub-18 Adding diagnostic plots for all ICA components to the HTML report …
│22:46:35│ ⏳️ sub-19 Fit 7 components (explaining 95.3% of the variance) in 3000 iterations.
│22:46:35│ ⏳️ sub-19 Saving ICA solution and detected artifacts to disk.
│22:46:35│ ⏳️ sub-19 Adding diagnostic plots for all ICA components to the HTML report …
│22:46:35│ ⏳️ sub-22 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:46:35│ ⏳️ sub-22 Calculating ICA solution using method: extended_infomax.
│22:46:35│ ⏳️ sub-23 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:46:36│ ⏳️ sub-23 Calculating ICA solution using method: extended_infomax.
│22:46:40│ ⏳️ sub-17 ICA completed. Please carefully review the extracted ICs in the report sub-17_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-17_task-SocialMemoryCuing_proc-ica_components.tsv
│22:46:40│ ⏳️ sub-24 Loading filtered raw data from sub-24_task-SocialMemoryCuing_proc-filt_raw
│22:46:40│ ⏳️ sub-24 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:46:41│ ⏳️ sub-24 No EOG channel is present. Cannot automate IC detection for EOG
│22:46:41│ ⏳️ sub-24 Applying high-pass filter with 1.0 Hz cutoff …
│22:46:41│ ⏳️ sub-24 Creating task-related epochs …
│22:46:42│ ⏳️ sub-21 ICA completed. Please carefully review the extracted ICs in the report sub-21_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-21_task-SocialMemoryCuing_proc-ica_components.tsv
│22:46:42│ ⏳️ sub-25 Loading filtered raw data from sub-25_task-SocialMemoryCuing_proc-filt_raw
│22:46:42│ ⏳️ sub-25 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:46:42│ ⏳️ sub-25 No EOG channel is present. Cannot automate IC detection for EOG
│22:46:42│ ⏳️ sub-25 Applying high-pass filter with 1.0 Hz cutoff …
│22:46:43│ ⏳️ sub-25 Creating task-related epochs …
│22:46:45│ ⏳️ sub-24 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:46:45│ ⏳️ sub-24 Calculating ICA solution using method: extended_infomax.
│22:46:47│ ⏳️ sub-18 ICA completed. Please carefully review the extracted ICs in the report sub-18_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-18_task-SocialMemoryCuing_proc-ica_components.tsv
│22:46:47│ ⏳️ sub-26 Loading filtered raw data from sub-26_task-SocialMemoryCuing_proc-filt_raw
│22:46:47│ ⏳️ sub-26 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:46:47│ ⏳️ sub-25 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:46:47│ ⏳️ sub-25 Calculating ICA solution using method: extended_infomax.
│22:46:47│ ⏳️ sub-26 No EOG channel is present. Cannot automate IC detection for EOG
│22:46:47│ ⏳️ sub-26 Applying high-pass filter with 1.0 Hz cutoff …
│22:46:47│ ⏳️ sub-23 Fit 6 components (explaining 95.1% of the variance) in 3000 iterations.
│22:46:48│ ⏳️ sub-23 Saving ICA solution and detected artifacts to disk.
│22:46:48│ ⏳️ sub-23 Adding diagnostic plots for all ICA components to the HTML report …
│22:46:48│ ⏳️ sub-19 ICA completed. Please carefully review the extracted ICs in the report sub-19_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-19_task-SocialMemoryCuing_proc-ica_components.tsv
│22:46:48│ ⏳️ sub-27 Loading filtered raw data from sub-27_task-SocialMemoryCuing_proc-filt_raw
│22:46:48│ ⏳️ sub-27 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:46:48│ ⏳️ sub-26 Creating task-related epochs …
│22:46:49│ ⏳️ sub-27 No EOG channel is present. Cannot automate IC detection for EOG
│22:46:49│ ⏳️ sub-27 Applying high-pass filter with 1.0 Hz cutoff …
│22:46:49│ ⏳️ sub-27 Creating task-related epochs …
│22:46:52│ ⏳️ sub-26 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:46:52│ ⏳️ sub-26 Calculating ICA solution using method: extended_infomax.
│22:46:53│ ⏳️ sub-27 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:46:53│ ⏳️ sub-27 Calculating ICA solution using method: extended_infomax.
│22:46:58│ ⏳️ sub-22 Fit 16 components (explaining 95.0% of the variance) in 3000 iterations.
│22:46:58│ ⏳️ sub-22 Saving ICA solution and detected artifacts to disk.
│22:46:58│ ⏳️ sub-22 Adding diagnostic plots for all ICA components to the HTML report …
│22:46:58│ ⏳️ sub-25 Fit 7 components (explaining 95.2% of the variance) in 3000 iterations.
│22:46:58│ ⏳️ sub-25 Saving ICA solution and detected artifacts to disk.
│22:46:58│ ⏳️ sub-25 Adding diagnostic plots for all ICA components to the HTML report …
│22:46:59│ ⏳️ sub-23 ICA completed. Please carefully review the extracted ICs in the report sub-23_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-23_task-SocialMemoryCuing_proc-ica_components.tsv
│22:46:59│ ⏳️ sub-28 Loading filtered raw data from sub-28_task-SocialMemoryCuing_proc-filt_raw
│22:46:59│ ⏳️ sub-28 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:46:59│ ⏳️ sub-28 No EOG channel is present. Cannot automate IC detection for EOG
│22:46:59│ ⏳️ sub-28 Applying high-pass filter with 1.0 Hz cutoff …
│22:47:00│ ⏳️ sub-28 Creating task-related epochs …
│22:47:00│ ⏳️ sub-24 Fit 11 components (explaining 95.3% of the variance) in 3000 iterations.
│22:47:00│ ⏳️ sub-24 Saving ICA solution and detected artifacts to disk.
│22:47:00│ ⏳️ sub-24 Adding diagnostic plots for all ICA components to the HTML report …
│22:47:05│ ⏳️ sub-28 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:47:05│ ⏳️ sub-28 Calculating ICA solution using method: extended_infomax.
│22:47:07│ ⏳️ sub-26 Fit 10 components (explaining 95.3% of the variance) in 3000 iterations.
│22:47:07│ ⏳️ sub-26 Saving ICA solution and detected artifacts to disk.
│22:47:07│ ⏳️ sub-26 Adding diagnostic plots for all ICA components to the HTML report …
│22:47:11│ ⏳️ sub-25 ICA completed. Please carefully review the extracted ICs in the report sub-25_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-25_task-SocialMemoryCuing_proc-ica_components.tsv
│22:47:11│ ⏳️ sub-30 Loading filtered raw data from sub-30_task-SocialMemoryCuing_proc-filt_raw
│22:47:11│ ⏳️ sub-30 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:47:11│ ⏳️ sub-30 No EOG channel is present. Cannot automate IC detection for EOG
│22:47:11│ ⏳️ sub-30 Applying high-pass filter with 1.0 Hz cutoff …
│22:47:12│ ⏳️ sub-30 Creating task-related epochs …
│22:47:16│ ⏳️ sub-24 ICA completed. Please carefully review the extracted ICs in the report sub-24_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-24_task-SocialMemoryCuing_proc-ica_components.tsv
│22:47:16│ ⏳️ sub-32 Loading filtered raw data from sub-32_task-SocialMemoryCuing_proc-filt_raw
│22:47:16│ ⏳️ sub-32 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:47:16│ ⏳️ sub-30 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:47:16│ ⏳️ sub-30 Calculating ICA solution using method: extended_infomax.
│22:47:16│ ⏳️ sub-32 No EOG channel is present. Cannot automate IC detection for EOG
│22:47:16│ ⏳️ sub-32 Applying high-pass filter with 1.0 Hz cutoff …
│22:47:17│ ⏳️ sub-32 Creating task-related epochs …
│22:47:21│ ⏳️ sub-32 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:47:21│ ⏳️ sub-32 Calculating ICA solution using method: extended_infomax.
│22:47:22│ ⏳️ sub-26 ICA completed. Please carefully review the extracted ICs in the report sub-26_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-26_task-SocialMemoryCuing_proc-ica_components.tsv
│22:47:22│ ⏳️ sub-33 Loading filtered raw data from sub-33_task-SocialMemoryCuing_proc-filt_raw
│22:47:22│ ⏳️ sub-33 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:47:22│ ⏳️ sub-33 No EOG channel is present. Cannot automate IC detection for EOG
│22:47:22│ ⏳️ sub-33 Applying high-pass filter with 1.0 Hz cutoff …
│22:47:23│ ⏳️ sub-33 Creating task-related epochs …
│22:47:24│ ⏳️ sub-27 Fit 15 components (explaining 95.0% of the variance) in 3000 iterations.
│22:47:24│ ⏳️ sub-27 Saving ICA solution and detected artifacts to disk.
│22:47:24│ ⏳️ sub-27 Adding diagnostic plots for all ICA components to the HTML report …
│22:47:24│ ⏳️ sub-22 ICA completed. Please carefully review the extracted ICs in the report sub-22_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-22_task-SocialMemoryCuing_proc-ica_components.tsv
│22:47:24│ ⏳️ sub-34 Loading filtered raw data from sub-34_task-SocialMemoryCuing_proc-filt_raw
│22:47:25│ ⏳️ sub-34 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:47:25│ ⏳️ sub-34 No EOG channel is present. Cannot automate IC detection for EOG
│22:47:25│ ⏳️ sub-34 Applying high-pass filter with 1.0 Hz cutoff …
│22:47:26│ ⏳️ sub-34 Creating task-related epochs …
│22:47:27│ ⏳️ sub-33 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:47:27│ ⏳️ sub-33 Calculating ICA solution using method: extended_infomax.
│22:47:31│ ⏳️ sub-34 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:47:31│ ⏳️ sub-34 Calculating ICA solution using method: extended_infomax.
│22:47:31│ ⏳️ sub-30 Fit 9 components (explaining 95.7% of the variance) in 3000 iterations.
│22:47:31│ ⏳️ sub-30 Saving ICA solution and detected artifacts to disk.
│22:47:31│ ⏳️ sub-30 Adding diagnostic plots for all ICA components to the HTML report …
│22:47:36│ ⏳️ sub-34 Fit 11 components (explaining 95.1% of the variance) in 3000 iterations.
│22:47:36│ ⏳️ sub-34 Saving ICA solution and detected artifacts to disk.
│22:47:36│ ⏳️ sub-34 Adding diagnostic plots for all ICA components to the HTML report …
│22:47:40│ ⏳️ sub-32 Fit 16 components (explaining 95.2% of the variance) in 3000 iterations.
│22:47:40│ ⏳️ sub-32 Saving ICA solution and detected artifacts to disk.
│22:47:40│ ⏳️ sub-32 Adding diagnostic plots for all ICA components to the HTML report …
│22:47:41│ ⏳️ sub-28 Fit 25 components (explaining 95.1% of the variance) in 3000 iterations.
│22:47:41│ ⏳️ sub-28 Saving ICA solution and detected artifacts to disk.
│22:47:41│ ⏳️ sub-28 Adding diagnostic plots for all ICA components to the HTML report …
│22:47:48│ ⏳️ sub-27 ICA completed. Please carefully review the extracted ICs in the report sub-27_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-27_task-SocialMemoryCuing_proc-ica_components.tsv
│22:47:48│ ⏳️ sub-35 Loading filtered raw data from sub-35_task-SocialMemoryCuing_proc-filt_raw
│22:47:48│ ⏳️ sub-35 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:47:48│ ⏳️ sub-35 No EOG channel is present. Cannot automate IC detection for EOG
│22:47:48│ ⏳️ sub-35 Applying high-pass filter with 1.0 Hz cutoff …
│22:47:48│ ⏳️ sub-30 ICA completed. Please carefully review the extracted ICs in the report sub-30_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-30_task-SocialMemoryCuing_proc-ica_components.tsv
│22:47:48│ ⏳️ sub-38 Loading filtered raw data from sub-38_task-SocialMemoryCuing_proc-filt_raw
│22:47:49│ ⏳️ sub-38 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:47:49│ ⏳️ sub-35 Creating task-related epochs …
│22:47:49│ ⏳️ sub-38 No EOG channel is present. Cannot automate IC detection for EOG
│22:47:49│ ⏳️ sub-38 Applying high-pass filter with 1.0 Hz cutoff …
│22:47:49│ ⏳️ sub-34 ICA completed. Please carefully review the extracted ICs in the report sub-34_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-34_task-SocialMemoryCuing_proc-ica_components.tsv
│22:47:49│ ⏳️ sub-39 Loading filtered raw data from sub-39_task-SocialMemoryCuing_proc-filt_raw
│22:47:49│ ⏳️ sub-39 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:47:49│ ⏳️ sub-39 No EOG channel is present. Cannot automate IC detection for EOG
│22:47:49│ ⏳️ sub-39 Applying high-pass filter with 1.0 Hz cutoff …
│22:47:50│ ⏳️ sub-38 Creating task-related epochs …
│22:47:50│ ⏳️ sub-39 Creating task-related epochs …
│22:47:53│ ⏳️ sub-35 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:47:53│ ⏳️ sub-35 Calculating ICA solution using method: extended_infomax.
│22:47:54│ ⏳️ sub-38 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:47:54│ ⏳️ sub-38 Calculating ICA solution using method: extended_infomax.
│22:47:55│ ⏳️ sub-39 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:47:55│ ⏳️ sub-39 Calculating ICA solution using method: extended_infomax.
│22:48:04│ ⏳️ sub-32 ICA completed. Please carefully review the extracted ICs in the report sub-32_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-32_task-SocialMemoryCuing_proc-ica_components.tsv
│22:48:04│ ⏳️ sub-40 Loading filtered raw data from sub-40_task-SocialMemoryCuing_proc-filt_raw
│22:48:04│ ⏳️ sub-40 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:48:05│ ⏳️ sub-40 No EOG channel is present. Cannot automate IC detection for EOG
│22:48:05│ ⏳️ sub-40 Applying high-pass filter with 1.0 Hz cutoff …
│22:48:05│ ⏳️ sub-40 Creating task-related epochs …
│22:48:06│ ⏳️ sub-35 Fit 6 components (explaining 95.2% of the variance) in 3000 iterations.
│22:48:06│ ⏳️ sub-35 Saving ICA solution and detected artifacts to disk.
│22:48:06│ ⏳️ sub-35 Adding diagnostic plots for all ICA components to the HTML report …
│22:48:06│ ⏳️ sub-38 Fit 6 components (explaining 95.2% of the variance) in 3000 iterations.
│22:48:06│ ⏳️ sub-38 Saving ICA solution and detected artifacts to disk.
│22:48:06│ ⏳️ sub-38 Adding diagnostic plots for all ICA components to the HTML report …
│22:48:09│ ⏳️ sub-33 Fit 13 components (explaining 95.2% of the variance) in 246 iterations.
│22:48:09│ ⏳️ sub-33 Saving ICA solution and detected artifacts to disk.
│22:48:09│ ⏳️ sub-39 Fit 8 components (explaining 95.3% of the variance) in 3000 iterations.
│22:48:09│ ⏳️ sub-39 Saving ICA solution and detected artifacts to disk.
│22:48:09│ ⏳️ sub-33 Adding diagnostic plots for all ICA components to the HTML report …
│22:48:09│ ⏳️ sub-39 Adding diagnostic plots for all ICA components to the HTML report …
│22:48:09│ ⏳️ sub-40 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:48:09│ ⏳️ sub-40 Calculating ICA solution using method: extended_infomax.
│22:48:16│ ⏳️ sub-28 ICA completed. Please carefully review the extracted ICs in the report sub-28_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-28_task-SocialMemoryCuing_proc-ica_components.tsv
│22:48:16│ ⏳️ sub-41 Loading filtered raw data from sub-41_task-SocialMemoryCuing_proc-filt_raw
│22:48:16│ ⏳️ sub-41 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:48:16│ ⏳️ sub-41 No EOG channel is present. Cannot automate IC detection for EOG
│22:48:16│ ⏳️ sub-41 Applying high-pass filter with 1.0 Hz cutoff …
│22:48:17│ ⏳️ sub-41 Creating task-related epochs …
│22:48:17│ ⏳️ sub-35 ICA completed. Please carefully review the extracted ICs in the report sub-35_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-35_task-SocialMemoryCuing_proc-ica_components.tsv
│22:48:17│ ⏳️ sub-43 Loading filtered raw data from sub-43_task-SocialMemoryCuing_proc-filt_raw
│22:48:17│ ⏳️ sub-43 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:48:18│ ⏳️ sub-43 No EOG channel is present. Cannot automate IC detection for EOG
│22:48:18│ ⏳️ sub-43 Applying high-pass filter with 1.0 Hz cutoff …
│22:48:18│ ⏳️ sub-38 ICA completed. Please carefully review the extracted ICs in the report sub-38_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-38_task-SocialMemoryCuing_proc-ica_components.tsv
│22:48:18│ ⏳️ sub-44 Loading filtered raw data from sub-44_task-SocialMemoryCuing_proc-filt_raw
│22:48:18│ ⏳️ sub-44 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:48:18│ ⏳️ sub-44 No EOG channel is present. Cannot automate IC detection for EOG
│22:48:18│ ⏳️ sub-44 Applying high-pass filter with 1.0 Hz cutoff …
│22:48:18│ ⏳️ sub-43 Creating task-related epochs …
│22:48:19│ ⏳️ sub-44 Creating task-related epochs …
│22:48:21│ ⏳️ sub-41 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:48:21│ ⏳️ sub-41 Calculating ICA solution using method: extended_infomax.
│22:48:21│ ⏳️ sub-40 Fit 7 components (explaining 95.3% of the variance) in 3000 iterations.
│22:48:21│ ⏳️ sub-40 Saving ICA solution and detected artifacts to disk.
│22:48:21│ ⏳️ sub-40 Adding diagnostic plots for all ICA components to the HTML report …
│22:48:22│ ⏳️ sub-39 ICA completed. Please carefully review the extracted ICs in the report sub-39_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-39_task-SocialMemoryCuing_proc-ica_components.tsv
│22:48:22│ ⏳️ sub-45 Loading filtered raw data from sub-45_task-SocialMemoryCuing_proc-filt_raw
│22:48:22│ ⏳️ sub-45 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:48:23│ ⏳️ sub-45 No EOG channel is present. Cannot automate IC detection for EOG
│22:48:23│ ⏳️ sub-45 Applying high-pass filter with 1.0 Hz cutoff …
│22:48:23│ ⏳️ sub-43 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:48:23│ ⏳️ sub-43 Calculating ICA solution using method: extended_infomax.
│22:48:23│ ⏳️ sub-45 Creating task-related epochs …
│22:48:23│ ⏳️ sub-44 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:48:23│ ⏳️ sub-44 Calculating ICA solution using method: extended_infomax.
│22:48:27│ ⏳️ sub-45 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:48:27│ ⏳️ sub-45 Calculating ICA solution using method: extended_infomax.
│22:48:28│ ⏳️ sub-33 ICA completed. Please carefully review the extracted ICs in the report sub-33_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-33_task-SocialMemoryCuing_proc-ica_components.tsv
│22:48:29│ ⏳️ sub-46 Loading filtered raw data from sub-46_task-SocialMemoryCuing_proc-filt_raw
│22:48:29│ ⏳️ sub-46 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:48:29│ ⏳️ sub-46 No EOG channel is present. Cannot automate IC detection for EOG
│22:48:29│ ⏳️ sub-46 Applying high-pass filter with 1.0 Hz cutoff …
│22:48:30│ ⏳️ sub-46 Creating task-related epochs …
│22:48:30│ ⏳️ sub-44 Fit 8 components (explaining 95.2% of the variance) in 3000 iterations.
│22:48:30│ ⏳️ sub-44 Saving ICA solution and detected artifacts to disk.
│22:48:31│ ⏳️ sub-44 Adding diagnostic plots for all ICA components to the HTML report …
│22:48:31│ ⏳️ sub-43 Fit 4 components (explaining 95.3% of the variance) in 3000 iterations.
│22:48:31│ ⏳️ sub-43 Saving ICA solution and detected artifacts to disk.
│22:48:31│ ⏳️ sub-43 Adding diagnostic plots for all ICA components to the HTML report …
│22:48:32│ ⏳️ sub-41 Fit 13 components (explaining 95.4% of the variance) in 3000 iterations.
│22:48:32│ ⏳️ sub-41 Saving ICA solution and detected artifacts to disk.
│22:48:32│ ⏳️ sub-41 Adding diagnostic plots for all ICA components to the HTML report …
│22:48:34│ ⏳️ sub-46 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:48:34│ ⏳️ sub-46 Calculating ICA solution using method: extended_infomax.
│22:48:34│ ⏳️ sub-40 ICA completed. Please carefully review the extracted ICs in the report sub-40_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-40_task-SocialMemoryCuing_proc-ica_components.tsv
│22:48:34│ ⏳️ sub-48 Loading filtered raw data from sub-48_task-SocialMemoryCuing_proc-filt_raw
│22:48:34│ ⏳️ sub-48 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:48:35│ ⏳️ sub-48 No EOG channel is present. Cannot automate IC detection for EOG
│22:48:35│ ⏳️ sub-48 Applying high-pass filter with 1.0 Hz cutoff …
│22:48:35│ ⏳️ sub-48 Creating task-related epochs …
│22:48:37│ ⏳️ sub-46 Fit 4 components (explaining 95.9% of the variance) in 3000 iterations.
│22:48:37│ ⏳️ sub-46 Saving ICA solution and detected artifacts to disk.
│22:48:37│ ⏳️ sub-46 Adding diagnostic plots for all ICA components to the HTML report …
│22:48:39│ ⏳️ sub-43 ICA completed. Please carefully review the extracted ICs in the report sub-43_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-43_task-SocialMemoryCuing_proc-ica_components.tsv
│22:48:39│ ⏳️ sub-49 Loading filtered raw data from sub-49_task-SocialMemoryCuing_proc-filt_raw
│22:48:39│ ⏳️ sub-48 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:48:39│ ⏳️ sub-48 Calculating ICA solution using method: extended_infomax.
│22:48:39│ ⏳️ sub-49 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:48:40│ ⏳️ sub-49 No EOG channel is present. Cannot automate IC detection for EOG
│22:48:40│ ⏳️ sub-49 Applying high-pass filter with 1.0 Hz cutoff …
│22:48:40│ ⏳️ sub-49 Creating task-related epochs …
│22:48:41│ ⏳️ sub-44 ICA completed. Please carefully review the extracted ICs in the report sub-44_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-44_task-SocialMemoryCuing_proc-ica_components.tsv
│22:48:41│ ⏳️ sub-50 Loading filtered raw data from sub-50_task-SocialMemoryCuing_proc-filt_raw
│22:48:41│ ⏳️ sub-50 No ECG or magnetometer channels are present. Cannot automate artifact detection for ECG
│22:48:41│ ⏳️ sub-50 No EOG channel is present. Cannot automate IC detection for EOG
│22:48:41│ ⏳️ sub-50 Applying high-pass filter with 1.0 Hz cutoff …
│22:48:41│ ⏳️ sub-45 Fit 10 components (explaining 95.2% of the variance) in 3000 iterations.
│22:48:41│ ⏳️ sub-45 Saving ICA solution and detected artifacts to disk.
│22:48:41│ ⏳️ sub-45 Adding diagnostic plots for all ICA components to the HTML report …
│22:48:42│ ⏳️ sub-50 Creating task-related epochs …
│22:48:43│ ⏳️ sub-46 ICA completed. Please carefully review the extracted ICs in the report sub-46_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-46_task-SocialMemoryCuing_proc-ica_components.tsv
│22:48:44│ ⏳️ sub-49 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:48:44│ ⏳️ sub-49 Calculating ICA solution using method: extended_infomax.
│22:48:46│ ⏳️ sub-50 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:48:46│ ⏳️ sub-50 Calculating ICA solution using method: extended_infomax.
│22:48:47│ ⏳️ sub-41 ICA completed. Please carefully review the extracted ICs in the report sub-41_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-41_task-SocialMemoryCuing_proc-ica_components.tsv
│22:48:47│ ⏳️ sub-48 Fit 10 components (explaining 95.2% of the variance) in 3000 iterations.
│22:48:47│ ⏳️ sub-48 Saving ICA solution and detected artifacts to disk.
│22:48:47│ ⏳️ sub-48 Adding diagnostic plots for all ICA components to the HTML report …
│22:48:50│ ⏳️ sub-49 Fit 6 components (explaining 95.9% of the variance) in 3000 iterations.
│22:48:50│ ⏳️ sub-49 Saving ICA solution and detected artifacts to disk.
│22:48:50│ ⏳️ sub-49 Adding diagnostic plots for all ICA components to the HTML report …
│22:48:55│ ⏳️ sub-45 ICA completed. Please carefully review the extracted ICs in the report sub-45_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-45_task-SocialMemoryCuing_proc-ica_components.tsv
│22:48:55│ ⏳️ sub-50 Fit 8 components (explaining 95.7% of the variance) in 3000 iterations.
│22:48:55│ ⏳️ sub-50 Saving ICA solution and detected artifacts to disk.
│22:48:55│ ⏳️ sub-50 Adding diagnostic plots for all ICA components to the HTML report …
│22:48:58│ ⏳️ sub-49 ICA completed. Please carefully review the extracted ICs in the report sub-49_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-49_task-SocialMemoryCuing_proc-ica_components.tsv
│22:48:58│ ⏳️ sub-48 ICA completed. Please carefully review the extracted ICs in the report sub-48_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-48_task-SocialMemoryCuing_proc-ica_components.tsv
│22:49:05│ ⏳️ sub-50 ICA completed. Please carefully review the extracted ICs in the report sub-50_task-SocialMemoryCuing_proc-ica+components_report.html, and mark all components you wish to reject as 'bad' in sub-50_task-SocialMemoryCuing_proc-ica_components.tsv
└────────┴ done (4m 17s)
In [70]:
# checkup: plot ica components
curr_checkup_ica = mne.preprocessing.read_ica(f"{curr_subject_path}/sub-01_task-SocialMemoryCuing_ica.fif")
curr_checkup_ica.apply(curr_checkup_raw_filtered)
curr_checkup_ica.plot_components(inst=curr_checkup_raw_filtered)
print("checkup: ICA component plots of the selected subject")
No description has been provided for this image 
checkup: ICA component plots of the selected subject

This checkup plot shows plots of ICA components. Since components can get plotted, the ICA has to have been successful.

These components seem to be related to different sources, including eye blinks and movement, noise, and looked-for activity within the brain.

ICA: Labelling¶

For automatic labelling of the components, the ICA label algorithms provided by the MNE framework get applied. The verbose version of the custom functions output is returned by this custom function. This is is followed by the content of a single subjects updated component label file.

Components labelled as brain or other are kept. These labels usually indicate, there are no or too few information for excluding the component.

Components labelled differently get marked as bad in the *.tsv file. Examples for such labels are muscle artifact, eye blink, and channel noise. The components labelled as bad are going to be excluded in the next step.

In [31]:
curr_steps = "preprocessing_apply_icalabel"
if curr_steps in STEPS_TO_RUN and STEPS_TO_RUN[curr_steps]:
    ih.update_ica_labels(cfg=cfg, do_print_verbose=True)


SUBJECT: 01
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 106212 samples), 14 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.8529084  0.78006613 0.9980018  0.83930933 0.28092322 0.54916686
 0.4785122  0.5192793  0.9846735  0.5491156  0.30257168 0.74395365
 0.49060318 0.36486763]

resulting labels:      ['eye blink', 'brain', 'eye blink', 'brain', 'eye blink', 'brain', 'other', 'eye blink', 'brain', 'brain', 'other', 'brain', 'other', 'brain']

old tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component   good                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN

new tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component    bad                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component    bad                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component    bad                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component    bad                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN


SUBJECT: 02
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 93687 samples), 23 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9551367  0.7941607  0.9832983  0.73693794 0.9619078  0.9972993
 0.8571708  0.9036504  0.44249463 0.3898017  0.95484656 0.5549054
 0.58458924 0.85234183 0.39791846 0.44918525 0.556823   0.48035112
 0.35887632 0.65801513 0.579979   0.47490945 0.37684757]

resulting labels:      ['eye blink', 'brain', 'brain', 'brain', 'brain', 'eye blink', 'brain', 'brain', 'muscle artifact', 'brain', 'brain', 'brain', 'brain', 'channel noise', 'muscle artifact', 'other', 'other', 'other', 'other', 'channel noise', 'brain', 'brain', 'other']

old tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component   good                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN
14         14  ica  Independent Component   good                 NaN
15         15  ica  Independent Component   good                 NaN
16         16  ica  Independent Component   good                 NaN
17         17  ica  Independent Component   good                 NaN
18         18  ica  Independent Component   good                 NaN
19         19  ica  Independent Component   good                 NaN
20         20  ica  Independent Component   good                 NaN
21         21  ica  Independent Component   good                 NaN
22         22  ica  Independent Component   good                 NaN

new tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component    bad                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component    bad                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component    bad                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component    bad                 NaN
14         14  ica  Independent Component    bad                 NaN
15         15  ica  Independent Component   good                 NaN
16         16  ica  Independent Component   good                 NaN
17         17  ica  Independent Component   good                 NaN
18         18  ica  Independent Component   good                 NaN
19         19  ica  Independent Component    bad                 NaN
20         20  ica  Independent Component   good                 NaN
21         21  ica  Independent Component   good                 NaN
22         22  ica  Independent Component   good                 NaN


SUBJECT: 03
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 88176 samples), 15 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.82363254 0.54587424 0.9968405  0.9429672  0.40769073 0.9963076
 0.5104217  0.9440704  0.7903057  0.3915435  0.7454948  0.65299827
 0.5953732  0.64983493 0.38313007]

resulting labels:      ['eye blink', 'channel noise', 'eye blink', 'brain', 'brain', 'brain', 'brain', 'brain', 'other', 'brain', 'brain', 'channel noise', 'other', 'other', 'other']

old tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component   good                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN
14         14  ica  Independent Component   good                 NaN

new tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component    bad                 NaN
1           1  ica  Independent Component    bad                 NaN
2           2  ica  Independent Component    bad                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component    bad                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN
14         14  ica  Independent Component   good                 NaN


SUBJECT: 04
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 111222 samples), 7 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.7475537  0.7190155  0.98949265 0.99888265 0.9982885  0.38094902
 0.5579004 ]

resulting labels:      ['eye blink', 'channel noise', 'brain', 'eye blink', 'brain', 'brain', 'other']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component    bad                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN


SUBJECT: 06
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 117234 samples), 20 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.8989463  0.42233926 0.9984003  0.356939   0.7337266  0.94103795
 0.9270439  0.8561232  0.6630374  0.40998268 0.37565178 0.5284235
 0.3119744  0.6401585  0.4891863  0.6896858  0.60043734 0.56177616
 0.35014844 0.42609474]

resulting labels:      ['eye blink', 'heart beat', 'eye blink', 'brain', 'brain', 'brain', 'brain', 'brain', 'brain', 'brain', 'channel noise', 'muscle artifact', 'other', 'other', 'brain', 'channel noise', 'other', 'channel noise', 'other', 'brain']

old tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component   good                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN
14         14  ica  Independent Component   good                 NaN
15         15  ica  Independent Component   good                 NaN
16         16  ica  Independent Component   good                 NaN
17         17  ica  Independent Component   good                 NaN
18         18  ica  Independent Component   good                 NaN
19         19  ica  Independent Component   good                 NaN

new tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component    bad                 NaN
1           1  ica  Independent Component    bad                 NaN
2           2  ica  Independent Component    bad                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component    bad                 NaN
11         11  ica  Independent Component    bad                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN
14         14  ica  Independent Component   good                 NaN
15         15  ica  Independent Component    bad                 NaN
16         16  ica  Independent Component   good                 NaN
17         17  ica  Independent Component    bad                 NaN
18         18  ica  Independent Component   good                 NaN
19         19  ica  Independent Component   good                 NaN


SUBJECT: 07
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 36072 samples), 8 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9204955  0.9961519  0.7357737  0.9565542  0.69889146 0.98295105
 0.61355555 0.32178408]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'brain', 'brain', 'brain', 'other', 'other']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN
7          7  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN
7          7  ica  Independent Component   good                 NaN


SUBJECT: 09
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 121743 samples), 7 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9685429  0.98260665 0.99073505 0.7116153  0.8720472  0.90883005
 0.57660353]

resulting labels:      ['eye blink', 'brain', 'eye blink', 'brain', 'brain', 'brain', 'brain']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component    bad                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN


SUBJECT: 10
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 113727 samples), 8 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9136653  0.999062   0.70231104 0.98197675 0.765229   0.89823437
 0.27466363 0.6107585 ]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'brain', 'brain', 'brain', 'eye blink', 'channel noise']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN
7          7  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component    bad                 NaN
7          7  ica  Independent Component    bad                 NaN


SUBJECT: 11
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 62124 samples), 9 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.95801485 0.99830794 0.94905853 0.8874153  0.91942    0.43757683
 0.9390304  0.92956567 0.2619439 ]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'brain', 'brain', 'brain', 'brain', 'other', 'channel noise']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN
7          7  ica  Independent Component   good                 NaN
8          8  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN
7          7  ica  Independent Component   good                 NaN
8          8  ica  Independent Component    bad                 NaN


SUBJECT: 12
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 119739 samples), 13 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.88934314 0.6499977  0.9343865  0.93933475 0.9991484  0.9447713
 0.9345404  0.3547498  0.3978842  0.9031575  0.5586442  0.28176665
 0.3443482 ]

resulting labels:      ['eye blink', 'brain', 'brain', 'brain', 'eye blink', 'brain', 'brain', 'heart beat', 'eye blink', 'brain', 'brain', 'other', 'other']

old tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component   good                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN

new tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component    bad                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component    bad                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component    bad                 NaN
8           8  ica  Independent Component    bad                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN


SUBJECT: 13
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 118737 samples), 15 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9645957  0.8642224  0.9989475  0.97787964 0.59187657 0.89711463
 0.71855843 0.85128415 0.98524106 0.42995858 0.42852908 0.81965053
 0.4543373  0.5948765  0.4277554 ]

resulting labels:      ['eye blink', 'brain', 'eye blink', 'brain', 'brain', 'brain', 'brain', 'brain', 'brain', 'brain', 'brain', 'channel noise', 'other', 'other', 'other']

old tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component   good                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN
14         14  ica  Independent Component   good                 NaN

new tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component    bad                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component    bad                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component    bad                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN
14         14  ica  Independent Component   good                 NaN


SUBJECT: 14
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 122244 samples), 7 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9775081  0.6809422  0.9990146  0.9796834  0.9499534  0.99012727
 0.7549843 ]

resulting labels:      ['eye blink', 'channel noise', 'eye blink', 'brain', 'brain', 'brain', 'brain']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component    bad                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN


SUBJECT: 15
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 113727 samples), 14 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9663899  0.9992591  0.46222922 0.9783709  0.89556724 0.3550663
 0.56904316 0.26091146 0.64409524 0.8812407  0.6509605  0.59016216
 0.4872961  0.48550725]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'brain', 'brain', 'brain', 'other', 'brain', 'brain', 'brain', 'brain', 'other', 'brain', 'other']

old tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component   good                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN

new tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component    bad                 NaN
1           1  ica  Independent Component    bad                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN


SUBJECT: 16
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 117234 samples), 7 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9589876  0.9521742  0.999406   0.6800357  0.9817233  0.99940765
 0.5085149 ]

resulting labels:      ['eye blink', 'brain', 'eye blink', 'brain', 'brain', 'brain', 'other']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component    bad                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN


SUBJECT: 17
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 113727 samples), 13 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.92959845 0.99843776 0.349171   0.5835215  0.91809815 0.95558023
 0.6457527  0.9777053  0.4694885  0.46546268 0.51636505 0.46516603
 0.57992935]

resulting labels:      ['eye blink', 'eye blink', 'channel noise', 'brain', 'brain', 'brain', 'brain', 'brain', 'brain', 'brain', 'brain', 'brain', 'channel noise']

old tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component   good                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN

new tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component    bad                 NaN
1           1  ica  Independent Component    bad                 NaN
2           2  ica  Independent Component    bad                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component    bad                 NaN


SUBJECT: 18
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 122244 samples), 7 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.97647697 0.99919266 0.9875828  0.67727506 0.97004014 0.7190341
 0.43694782]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'brain', 'brain', 'brain', 'other']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN


SUBJECT: 19
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 119739 samples), 7 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9994774  0.90444285 0.84365416 0.82658774 0.82537925 0.57328033
 0.75796866]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'brain', 'brain', 'eye blink', 'brain']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component    bad                 NaN
6          6  ica  Independent Component   good                 NaN


SUBJECT: 21
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 79158 samples), 5 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.97932196 0.99788696 0.88402146 0.9663782  0.37255055]

resulting labels:      ['eye blink', 'eye blink', 'channel noise', 'brain', 'heart beat']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component    bad                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component    bad                 NaN


SUBJECT: 22
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 115731 samples), 16 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.93190336 0.8706529  0.99894285 0.9370656  0.8927633  0.79573834
 0.5446112  0.79574263 0.9974796  0.4727111  0.90672064 0.48256496
 0.9247676  0.53599983 0.5038415  0.34740075]

resulting labels:      ['eye blink', 'brain', 'eye blink', 'brain', 'muscle artifact', 'other', 'other', 'brain', 'brain', 'eye blink', 'other', 'other', 'other', 'brain', 'brain', 'other']

old tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component   good                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN
14         14  ica  Independent Component   good                 NaN
15         15  ica  Independent Component   good                 NaN

new tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component    bad                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component    bad                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component    bad                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component    bad                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN
14         14  ica  Independent Component   good                 NaN
15         15  ica  Independent Component   good                 NaN


SUBJECT: 23
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 114228 samples), 6 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.97670233 0.99917144 0.8099412  0.24760397 0.8300717  0.48979932]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'channel noise', 'brain', 'muscle artifact']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component    bad                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component    bad                 NaN


SUBJECT: 24
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 99699 samples), 11 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.968665   0.4965744  0.99958384 0.9752158  0.9337271  0.87431
 0.95093656 0.99667037 0.97131634 0.26318574 0.7244801 ]

resulting labels:      ['eye blink', 'brain', 'eye blink', 'brain', 'brain', 'brain', 'brain', 'brain', 'muscle artifact', 'other', 'muscle artifact']

old tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component   good                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN

new tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component    bad                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component    bad                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component    bad                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component    bad                 NaN


SUBJECT: 25
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 107214 samples), 7 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9599041  0.99892586 0.682561   0.9644024  0.56496775 0.97633207
 0.56551033]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'brain', 'brain', 'brain', 'other']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN


SUBJECT: 26
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 109218 samples), 10 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9543836  0.9947903  0.77129817 0.36532164 0.82779926 0.49062878
 0.8036537  0.5095811  0.6293426  0.8739162 ]

resulting labels:      ['eye blink', 'eye blink', 'muscle artifact', 'brain', 'brain', 'channel noise', 'brain', 'muscle artifact', 'other', 'muscle artifact']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN
7          7  ica  Independent Component   good                 NaN
8          8  ica  Independent Component   good                 NaN
9          9  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component    bad                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component    bad                 NaN
6          6  ica  Independent Component   good                 NaN
7          7  ica  Independent Component    bad                 NaN
8          8  ica  Independent Component   good                 NaN
9          9  ica  Independent Component    bad                 NaN


SUBJECT: 27
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 118236 samples), 15 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9606969  0.544942   0.99846524 0.9954375  0.9977177  0.9386366
 0.9633286  0.82140326 0.89666975 0.9715538  0.944155   0.70885944
 0.3839414  0.52708846 0.5611132 ]

resulting labels:      ['eye blink', 'other', 'eye blink', 'brain', 'brain', 'other', 'muscle artifact', 'channel noise', 'brain', 'muscle artifact', 'muscle artifact', 'brain', 'brain', 'other', 'brain']

old tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component   good                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN
14         14  ica  Independent Component   good                 NaN

new tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component    bad                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component    bad                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component    bad                 NaN
7           7  ica  Independent Component    bad                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component    bad                 NaN
10         10  ica  Independent Component    bad                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN
14         14  ica  Independent Component   good                 NaN


SUBJECT: 28
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 121743 samples), 25 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.946444   0.96390545 0.9525249  0.35485208 0.9975654  0.9798029
 0.44921404 0.68858767 0.8498612  0.70428485 0.8843539  0.59858125
 0.38636672 0.86854887 0.6802094  0.611169   0.44242865 0.9122539
 0.4096762  0.47560155 0.46677327 0.7190976  0.6061458  0.77444315
 0.53866583]

resulting labels:      ['eye blink', 'brain', 'brain', 'heart beat', 'eye blink', 'brain', 'brain', 'brain', 'other', 'other', 'brain', 'brain', 'other', 'channel noise', 'other', 'brain', 'other', 'other', 'brain', 'brain', 'channel noise', 'channel noise', 'other', 'channel noise', 'brain']

old tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component   good                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN
14         14  ica  Independent Component   good                 NaN
15         15  ica  Independent Component   good                 NaN
16         16  ica  Independent Component   good                 NaN
17         17  ica  Independent Component   good                 NaN
18         18  ica  Independent Component   good                 NaN
19         19  ica  Independent Component   good                 NaN
20         20  ica  Independent Component   good                 NaN
21         21  ica  Independent Component   good                 NaN
22         22  ica  Independent Component   good                 NaN
23         23  ica  Independent Component   good                 NaN
24         24  ica  Independent Component   good                 NaN

new tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component    bad                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component    bad                 NaN
4           4  ica  Independent Component    bad                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component    bad                 NaN
14         14  ica  Independent Component   good                 NaN
15         15  ica  Independent Component   good                 NaN
16         16  ica  Independent Component   good                 NaN
17         17  ica  Independent Component   good                 NaN
18         18  ica  Independent Component   good                 NaN
19         19  ica  Independent Component   good                 NaN
20         20  ica  Independent Component    bad                 NaN
21         21  ica  Independent Component    bad                 NaN
22         22  ica  Independent Component   good                 NaN
23         23  ica  Independent Component    bad                 NaN
24         24  ica  Independent Component   good                 NaN


SUBJECT: 30
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 122244 samples), 9 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9710359  0.5125391  0.9994741  0.9758337  0.91214556 0.5593158
 0.6116842  0.83049893 0.5473498 ]

resulting labels:      ['eye blink', 'brain', 'eye blink', 'brain', 'brain', 'other', 'brain', 'brain', 'brain']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN
7          7  ica  Independent Component   good                 NaN
8          8  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component    bad                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN
7          7  ica  Independent Component   good                 NaN
8          8  ica  Independent Component   good                 NaN


SUBJECT: 32
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 95691 samples), 16 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9779614  0.49421844 0.9982132  0.89567196 0.27898023 0.9262517
 0.9754737  0.34698537 0.8225404  0.536206   0.414869   0.33290955
 0.5775435  0.7253194  0.36261117 0.46845478]

resulting labels:      ['eye blink', 'channel noise', 'eye blink', 'brain', 'other', 'brain', 'brain', 'other', 'other', 'muscle artifact', 'brain', 'other', 'brain', 'other', 'other', 'other']

old tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component   good                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN
14         14  ica  Independent Component   good                 NaN
15         15  ica  Independent Component   good                 NaN

new tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component    bad                 NaN
1           1  ica  Independent Component    bad                 NaN
2           2  ica  Independent Component    bad                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component    bad                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN
13         13  ica  Independent Component   good                 NaN
14         14  ica  Independent Component   good                 NaN
15         15  ica  Independent Component   good                 NaN


SUBJECT: 33
<ICA | epochs decomposition, method: infomax (fit in 246 iterations on 121743 samples), 13 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.963784   0.9990411  0.66625994 0.9809519  0.4094605  0.93102443
 0.920706   0.70845646 0.79939175 0.7917919  0.43748862 0.9449089
 0.9310027 ]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'brain', 'channel noise', 'brain', 'brain', 'muscle artifact', 'other', 'other', 'brain', 'other', 'other']

old tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component   good                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN

new tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component    bad                 NaN
1           1  ica  Independent Component    bad                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component    bad                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component    bad                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN


SUBJECT: 34
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 26553 samples), 11 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9142765  0.99101704 0.5263203  0.4102772  0.53291595 0.8723508
 0.7856613  0.82970107 0.32133806 0.96176    0.56586564]

resulting labels:      ['eye blink', 'eye blink', 'channel noise', 'eye blink', 'brain', 'brain', 'brain', 'muscle artifact', 'muscle artifact', 'eye blink', 'muscle artifact']

old tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component   good                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN

new tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component    bad                 NaN
1           1  ica  Independent Component    bad                 NaN
2           2  ica  Independent Component    bad                 NaN
3           3  ica  Independent Component    bad                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component    bad                 NaN
8           8  ica  Independent Component    bad                 NaN
9           9  ica  Independent Component    bad                 NaN
10         10  ica  Independent Component    bad                 NaN


SUBJECT: 35
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 120741 samples), 6 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.95282763 0.99946934 0.5133801  0.9885143  0.9943621  0.7987275 ]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'brain', 'brain', 'brain']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN


SUBJECT: 38
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 120240 samples), 6 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.969628   0.99843365 0.96550834 0.9983072  0.9982072  0.9380568 ]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'brain', 'brain', 'brain']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN


SUBJECT: 39
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 122244 samples), 8 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9603301  0.9994427  0.5771604  0.9714781  0.96544677 0.9775326
 0.9185418  0.584869  ]

resulting labels:      ['eye blink', 'eye blink', 'channel noise', 'brain', 'brain', 'brain', 'muscle artifact', 'muscle artifact']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN
7          7  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component    bad                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component    bad                 NaN
7          7  ica  Independent Component    bad                 NaN


SUBJECT: 40
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 120240 samples), 7 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9698907  0.9992361  0.59660363 0.98960096 0.99959457 0.99901927
 0.99803144]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'brain', 'brain', 'brain', 'brain']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN


SUBJECT: 41
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 59118 samples), 13 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.8604021  0.9981775  0.8995439  0.6456953  0.31347513 0.4777335
 0.5758145  0.5769622  0.35491636 0.36632913 0.46324205 0.3415593
 0.40360695]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'other', 'brain', 'brain', 'brain', 'other', 'muscle artifact', 'brain', 'other', 'eye blink', 'muscle artifact']

old tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component   good                 NaN
1           1  ica  Independent Component   good                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component   good                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component   good                 NaN
12         12  ica  Independent Component   good                 NaN

new tsv file content:
    component type            description status  status_description
0           0  ica  Independent Component    bad                 NaN
1           1  ica  Independent Component    bad                 NaN
2           2  ica  Independent Component   good                 NaN
3           3  ica  Independent Component   good                 NaN
4           4  ica  Independent Component   good                 NaN
5           5  ica  Independent Component   good                 NaN
6           6  ica  Independent Component   good                 NaN
7           7  ica  Independent Component   good                 NaN
8           8  ica  Independent Component    bad                 NaN
9           9  ica  Independent Component   good                 NaN
10         10  ica  Independent Component   good                 NaN
11         11  ica  Independent Component    bad                 NaN
12         12  ica  Independent Component    bad                 NaN


SUBJECT: 43
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 99198 samples), 4 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.96766293 0.9970876  0.9103731  0.8834447 ]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'brain']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN


SUBJECT: 44
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 58617 samples), 8 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.96985656 0.9890049  0.9671366  0.99255943 0.9732714  0.5044676
 0.9547269  0.9982488 ]

resulting labels:      ['eye blink', 'muscle artifact', 'muscle artifact', 'eye blink', 'muscle artifact', 'channel noise', 'muscle artifact', 'brain']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN
7          7  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component    bad                 NaN
3          3  ica  Independent Component    bad                 NaN
4          4  ica  Independent Component    bad                 NaN
5          5  ica  Independent Component    bad                 NaN
6          6  ica  Independent Component    bad                 NaN
7          7  ica  Independent Component   good                 NaN


SUBJECT: 45
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 111222 samples), 10 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.907248   0.9949111  0.5050391  0.43150812 0.85397285 0.59204227
 0.97683513 0.5619394  0.93748164 0.53061974]

resulting labels:      ['eye blink', 'eye blink', 'channel noise', 'brain', 'brain', 'muscle artifact', 'brain', 'brain', 'muscle artifact', 'muscle artifact']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN
7          7  ica  Independent Component   good                 NaN
8          8  ica  Independent Component   good                 NaN
9          9  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component    bad                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component    bad                 NaN
6          6  ica  Independent Component   good                 NaN
7          7  ica  Independent Component   good                 NaN
8          8  ica  Independent Component    bad                 NaN
9          9  ica  Independent Component    bad                 NaN


SUBJECT: 46
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 29559 samples), 4 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9748526  0.99912745 0.9979217  0.99801904]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'brain']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN


SUBJECT: 48
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 57114 samples), 10 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.98390305 0.9993767  0.8977916  0.8117123  0.97363406 0.78229564
 0.69085115 0.9195261  0.57272315 0.38760328]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'brain', 'brain', 'channel noise', 'channel noise', 'brain', 'other', 'channel noise']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN
7          7  ica  Independent Component   good                 NaN
8          8  ica  Independent Component   good                 NaN
9          9  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component    bad                 NaN
6          6  ica  Independent Component    bad                 NaN
7          7  ica  Independent Component   good                 NaN
8          8  ica  Independent Component   good                 NaN
9          9  ica  Independent Component    bad                 NaN


SUBJECT: 49
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 58116 samples), 6 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.9533707  0.9981717  0.93970907 0.9949904  0.44783533 0.78087497]

resulting labels:      ['eye blink', 'eye blink', 'brain', 'brain', 'brain', 'brain']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN


SUBJECT: 50
<ICA | epochs decomposition, method: infomax (fit in 3000 iterations on 89679 samples), 8 ICA components (63 PCA components available), channel types: eeg, no sources marked for exclusion>

resulting predictions: [0.95787346 0.99867654 0.5828493  0.9617361  0.44849527 0.4684739
 0.31816778 0.5279835 ]

resulting labels:      ['eye blink', 'eye blink', 'channel noise', 'brain', 'muscle artifact', 'other', 'channel noise', 'eye blink']

old tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component   good                 NaN
1          1  ica  Independent Component   good                 NaN
2          2  ica  Independent Component   good                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component   good                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component   good                 NaN
7          7  ica  Independent Component   good                 NaN

new tsv file content:
   component type            description status  status_description
0          0  ica  Independent Component    bad                 NaN
1          1  ica  Independent Component    bad                 NaN
2          2  ica  Independent Component    bad                 NaN
3          3  ica  Independent Component   good                 NaN
4          4  ica  Independent Component    bad                 NaN
5          5  ica  Independent Component   good                 NaN
6          6  ica  Independent Component    bad                 NaN
7          7  ica  Independent Component    bad                 NaN
In [32]:
# checkup: print list of components given in updated …_proc-ica+components.tsv file
#!cat "{curr_subject_path}/sub-01_task-SocialMemoryCuing_proc-ica_components.tsv"
cmd.cat(curr_subject_path + "/sub-01_task-SocialMemoryCuing_proc-ica_components.tsv")
# This file should contain a status like "bad" for eye blinks, or "good" for brain activity, as it is indicated above and visible in the ICA component plots.

component	type	description	status	status_description

0	ica	Independent Component	bad	

1	ica	Independent Component	good	

2	ica	Independent Component	bad	

3	ica	Independent Component	good	

4	ica	Independent Component	bad	

5	ica	Independent Component	good	

6	ica	Independent Component	good	

7	ica	Independent Component	bad	

8	ica	Independent Component	good	

9	ica	Independent Component	good	

10	ica	Independent Component	good	

11	ica	Independent Component	good	

12	ica	Independent Component	good	

13	ica	Independent Component	good

This checkup prints the components of a subject with status in {good, bad}. Since both labels are given, while the initial setup contains only good for all commponents, the ICA label software seems to work.

ICA: Cleaning¶

Based on the component labels, the signals of the corresponding subject get cleaned.

The resulting epoch signals get plotted in comparison to the not-ICA-cleaned epoch signals as checkup. The amplitude of the epoch signals is visualised based on the colourbar on the right hand side. This colourbar is independent per plot. Therefore, the scale should be kept in mind while comparing versions.

In [33]:
curr_steps = "preprocessing/_07a_apply_ica"
if curr_steps in STEPS_TO_RUN and STEPS_TO_RUN[curr_steps]:
    !mne_bids_pipeline --config {config_path} --steps {curr_steps}

┌────────┬ Welcome aboard MNE-BIDS-Pipeline! 👋 ────────────────────────────────
│22:50:32│ 📝 Using configuration: ./mne-bids/config/mne-bids-pipeline.py
└────────┴ 
┌────────┬ init/_01_init_derivatives_dir ───────────────────────────────────────
│22:50:32│ ✅ Output directories already exist …
└────────┴ done (1s)
┌────────┬ init/_02_find_empty_room ────────────────────────────────────────────
│22:50:33│ ⏩ Skipping, empty-room data only relevant for MEG …
└────────┴ done (1s)
┌────────┬ preprocessing/_07a_apply_ica ────────────────────────────────────────
│22:50:34│ ⏳️ sub-06 Input: sub-06_task-SocialMemoryCuing_epo.fif
│22:50:34│ ⏳️ sub-02 Input: sub-02_task-SocialMemoryCuing_epo.fif
│22:50:34│ ⏳️ sub-02 Output: sub-02_task-SocialMemoryCuing_proc-ica_epo.fif
│22:50:34│ ⏳️ sub-06 Output: sub-06_task-SocialMemoryCuing_proc-ica_epo.fif
│22:50:34│ ⏳️ sub-01 Input: sub-01_task-SocialMemoryCuing_epo.fif
│22:50:34│ ⏳️ sub-01 Output: sub-01_task-SocialMemoryCuing_proc-ica_epo.fif
│22:50:34│ ⏳️ sub-03 Input: sub-03_task-SocialMemoryCuing_epo.fif
│22:50:34│ ⏳️ sub-03 Output: sub-03_task-SocialMemoryCuing_proc-ica_epo.fif
│22:50:34│ ⏳️ sub-04 Input: sub-04_task-SocialMemoryCuing_epo.fif
│22:50:34│ ⏳️ sub-04 Output: sub-04_task-SocialMemoryCuing_proc-ica_epo.fif
│22:50:34│ ⏳️ sub-02 Rejecting ICs: 0, 5, 8, 13, 14, 19
│22:50:34│ ⏳️ sub-06 Rejecting ICs: 0, 1, 2, 10, 11, 15, 17
│22:50:34│ ⏳️ sub-07 Input: sub-07_task-SocialMemoryCuing_epo.fif
│22:50:34│ ⏳️ sub-01 Rejecting ICs: 0, 2, 4, 7
│22:50:34│ ⏳️ sub-03 Rejecting ICs: 0, 1, 2, 11
│22:50:34│ ⏳️ sub-07 Output: sub-07_task-SocialMemoryCuing_proc-ica_epo.fif
│22:50:34│ ⏳️ sub-04 Rejecting ICs: 0, 1, 3
│22:50:34│ ⏳️ sub-06 Saving reconstructed epochs after ICA.
│22:50:34│ ⏳️ sub-07 Rejecting ICs: 0, 1
│22:50:34│ ⏳️ sub-02 Saving reconstructed epochs after ICA.
│22:50:35│ ⏳️ sub-03 Saving reconstructed epochs after ICA.
│22:50:35│ ⏳️ sub-01 Saving reconstructed epochs after ICA.
│22:50:35│ ⏳️ sub-04 Saving reconstructed epochs after ICA.
│22:50:35│ ⏳️ sub-07 Saving reconstructed epochs after ICA.
│22:50:38│ ⏳️ sub-07 Adding ICA to report.
│22:50:39│ ⏳️ sub-04 Adding ICA to report.
│22:50:40│ ⏳️ sub-03 Adding ICA to report.
│22:50:41│ ⏳️ sub-01 Adding ICA to report.
│22:50:41│ ⏳️ sub-07 Adding config and sys info to report
│22:50:42│ ⏳️ sub-02 Adding ICA to report.
│22:50:43│ ⏳️ sub-04 Adding config and sys info to report
│22:50:43│ ⏳️ sub-06 Adding ICA to report.
│22:50:44│ ⏳️ sub-07 Saving report: ]8;id=703937;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=168564;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=423937;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\(]8;;\]8;id=914923;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=423937;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\)]8;;\]8;id=703937;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/]8;;\]8;id=168564;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\sub-07_task-SocialMemoryCuing_report.html]8;;\
│22:50:44│ ⏳️ sub-09 Input: sub-09_task-SocialMemoryCuing_epo.fif
│22:50:44│ ⏳️ sub-09 Output: sub-09_task-SocialMemoryCuing_proc-ica_epo.fif
│22:50:44│ ⏳️ sub-09 Rejecting ICs: 0, 2
│22:50:44│ ⏳️ sub-09 Saving reconstructed epochs after ICA.
│22:50:45│ ⏳️ sub-03 Adding config and sys info to report
│22:50:46│ ⏳️ sub-01 Adding config and sys info to report
│22:50:46│ ⏳️ sub-04 Saving report: ]8;id=965514;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=638955;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=156794;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\(]8;;\]8;id=563094;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=156794;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\)]8;;\]8;id=965514;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/]8;;\]8;id=638955;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\sub-04_task-SocialMemoryCuing_report.html]8;;\
│22:50:46│ ⏳️ sub-10 Input: sub-10_task-SocialMemoryCuing_epo.fif
│22:50:46│ ⏳️ sub-10 Output: sub-10_task-SocialMemoryCuing_proc-ica_epo.fif
│22:50:46│ ⏳️ sub-10 Rejecting ICs: 0, 1, 6, 7
│22:50:47│ ⏳️ sub-10 Saving reconstructed epochs after ICA.
│22:50:48│ ⏳️ sub-03 Saving report: ]8;id=28713;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=319121;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=247544;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\(]8;;\]8;id=891087;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=247544;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\)]8;;\]8;id=28713;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/]8;;\]8;id=319121;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\sub-03_task-SocialMemoryCuing_report.html]8;;\
│22:50:48│ ⏳️ sub-09 Adding ICA to report.
│22:50:48│ ⏳️ sub-11 Input: sub-11_task-SocialMemoryCuing_epo.fif
│22:50:48│ ⏳️ sub-11 Output: sub-11_task-SocialMemoryCuing_proc-ica_epo.fif
│22:50:48│ ⏳️ sub-11 Rejecting ICs: 0, 1, 8
│22:50:48│ ⏳️ sub-01 Saving report: ]8;id=896400;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=55951;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=748196;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\(]8;;\]8;id=904521;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=748196;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\)]8;;\]8;id=896400;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/]8;;\]8;id=55951;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\sub-01_task-SocialMemoryCuing_report.html]8;;\
│22:50:48│ ⏳️ sub-11 Saving reconstructed epochs after ICA.
│22:50:49│ ⏳️ sub-12 Input: sub-12_task-SocialMemoryCuing_epo.fif
│22:50:49│ ⏳️ sub-12 Output: sub-12_task-SocialMemoryCuing_proc-ica_epo.fif
│22:50:49│ ⏳️ sub-12 Rejecting ICs: 0, 4, 7, 8
│22:50:49│ ⏳️ sub-12 Saving reconstructed epochs after ICA.
│22:50:50│ ⏳️ sub-02 Adding config and sys info to report
│22:50:51│ ⏳️ sub-09 Adding config and sys info to report
│22:50:51│ ⏳️ sub-09 Saving report: ]8;id=128133;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-09/eeg/sub-09_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=420518;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-09/eeg/sub-09_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=967826;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-09/eeg/sub-09_task-SocialMemoryCuing_report.html\(]8;;\]8;id=801030;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-09/eeg/sub-09_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=967826;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-09/eeg/sub-09_task-SocialMemoryCuing_report.html\)]8;;\]8;id=128133;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-09/eeg/sub-09_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-09/eeg/]8;;\]8;id=420518;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-09/eeg/sub-09_task-SocialMemoryCuing_report.html\sub-09_task-SocialMemoryCuing_report.html]8;;\
│22:50:51│ ⏳️ sub-13 Input: sub-13_task-SocialMemoryCuing_epo.fif
│22:50:51│ ⏳️ sub-13 Output: sub-13_task-SocialMemoryCuing_proc-ica_epo.fif
│22:50:51│ ⏳️ sub-13 Rejecting ICs: 0, 2, 11
│22:50:52│ ⏳️ sub-13 Saving reconstructed epochs after ICA.
│22:50:52│ ⏳️ sub-10 Adding ICA to report.
│22:50:52│ ⏳️ sub-06 Adding config and sys info to report
│22:50:53│ ⏳️ sub-11 Adding ICA to report.
│22:50:53│ ⏳️ sub-02 Saving report: ]8;id=303154;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=178003;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=127426;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\(]8;;\]8;id=499385;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=127426;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\)]8;;\]8;id=303154;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/]8;;\]8;id=178003;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\sub-02_task-SocialMemoryCuing_report.html]8;;\
│22:50:53│ ⏳️ sub-14 Input: sub-14_task-SocialMemoryCuing_epo.fif
│22:50:53│ ⏳️ sub-14 Output: sub-14_task-SocialMemoryCuing_proc-ica_epo.fif
│22:50:53│ ⏳️ sub-14 Rejecting ICs: 0, 1, 2
│22:50:53│ ⏳️ sub-14 Saving reconstructed epochs after ICA.
│22:50:54│ ⏳️ sub-12 Adding ICA to report.
│22:50:55│ ⏳️ sub-06 Saving report: ]8;id=425065;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=441306;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=645120;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\(]8;;\]8;id=943823;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=645120;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\)]8;;\]8;id=425065;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/]8;;\]8;id=441306;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\sub-06_task-SocialMemoryCuing_report.html]8;;\
│22:50:55│ ⏳️ sub-15 Input: sub-15_task-SocialMemoryCuing_epo.fif
│22:50:55│ ⏳️ sub-15 Output: sub-15_task-SocialMemoryCuing_proc-ica_epo.fif
│22:50:55│ ⏳️ sub-15 Rejecting ICs: 0, 1
│22:50:55│ ⏳️ sub-15 Saving reconstructed epochs after ICA.
│22:50:56│ ⏳️ sub-13 Adding ICA to report.
│22:50:57│ ⏳️ sub-11 Adding config and sys info to report
│22:50:57│ ⏳️ sub-11 Saving report: ]8;id=336736;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=417;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=633653;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\(]8;;\]8;id=847871;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=633653;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\)]8;;\]8;id=336736;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/]8;;\]8;id=417;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\sub-11_task-SocialMemoryCuing_report.html]8;;\
│22:50:57│ ⏳️ sub-16 Input: sub-16_task-SocialMemoryCuing_epo.fif
│22:50:57│ ⏳️ sub-16 Output: sub-16_task-SocialMemoryCuing_proc-ica_epo.fif
│22:50:57│ ⏳️ sub-10 Adding config and sys info to report
│22:50:57│ ⏳️ sub-16 Rejecting ICs: 0, 2
│22:50:57│ ⏳️ sub-10 Saving report: ]8;id=510304;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=571210;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=914669;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\(]8;;\]8;id=206416;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=914669;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\)]8;;\]8;id=510304;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/]8;;\]8;id=571210;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\sub-10_task-SocialMemoryCuing_report.html]8;;\
│22:50:57│ ⏳️ sub-16 Saving reconstructed epochs after ICA.
│22:50:57│ ⏳️ sub-17 Input: sub-17_task-SocialMemoryCuing_epo.fif
│22:50:57│ ⏳️ sub-17 Output: sub-17_task-SocialMemoryCuing_proc-ica_epo.fif
│22:50:57│ ⏳️ sub-17 Rejecting ICs: 0, 1, 2, 12
│22:50:57│ ⏳️ sub-17 Saving reconstructed epochs after ICA.
│22:50:58│ ⏳️ sub-14 Adding ICA to report.
│22:50:58│ ⏳️ sub-15 Adding ICA to report.
│22:51:00│ ⏳️ sub-12 Adding config and sys info to report
│22:51:00│ ⏳️ sub-12 Saving report: ]8;id=704510;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=389653;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=650182;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\(]8;;\]8;id=356033;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=650182;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\)]8;;\]8;id=704510;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/]8;;\]8;id=389653;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\sub-12_task-SocialMemoryCuing_report.html]8;;\
│22:51:00│ ⏳️ sub-13 Adding config and sys info to report
│22:51:00│ ⏳️ sub-13 Saving report: ]8;id=783168;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=446703;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=774427;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\(]8;;\]8;id=243627;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=774427;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\)]8;;\]8;id=783168;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/]8;;\]8;id=446703;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\sub-13_task-SocialMemoryCuing_report.html]8;;\
│22:51:00│ ⏳️ sub-18 Input: sub-18_task-SocialMemoryCuing_epo.fif
│22:51:00│ ⏳️ sub-19 Input: sub-19_task-SocialMemoryCuing_epo.fif
│22:51:00│ ⏳️ sub-18 Output: sub-18_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:00│ ⏳️ sub-19 Output: sub-19_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:00│ ⏳️ sub-18 Rejecting ICs: 0, 1
│22:51:00│ ⏳️ sub-19 Rejecting ICs: 0, 1, 5
│22:51:00│ ⏳️ sub-16 Adding ICA to report.
│22:51:00│ ⏳️ sub-19 Saving reconstructed epochs after ICA.
│22:51:00│ ⏳️ sub-18 Saving reconstructed epochs after ICA.
│22:51:01│ ⏳️ sub-15 Adding config and sys info to report
│22:51:01│ ⏳️ sub-15 Saving report: ]8;id=735427;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=617399;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=978972;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\(]8;;\]8;id=730155;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=978972;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\)]8;;\]8;id=735427;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/]8;;\]8;id=617399;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\sub-15_task-SocialMemoryCuing_report.html]8;;\
│22:51:01│ ⏳️ sub-21 Input: sub-21_task-SocialMemoryCuing_epo.fif
│22:51:01│ ⏳️ sub-21 Output: sub-21_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:02│ ⏳️ sub-21 Rejecting ICs: 0, 1, 2, 4
│22:51:02│ ⏳️ sub-14 Adding config and sys info to report
│22:51:02│ ⏳️ sub-14 Saving report: ]8;id=868676;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=681557;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=117040;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\(]8;;\]8;id=758474;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=117040;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\)]8;;\]8;id=868676;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/]8;;\]8;id=681557;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\sub-14_task-SocialMemoryCuing_report.html]8;;\
│22:51:02│ ⏳️ sub-21 Saving reconstructed epochs after ICA.
│22:51:02│ ⏳️ sub-22 Input: sub-22_task-SocialMemoryCuing_epo.fif
│22:51:02│ ⏳️ sub-22 Output: sub-22_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:02│ ⏳️ sub-22 Rejecting ICs: 0, 2, 4, 9
│22:51:02│ ⏳️ sub-22 Saving reconstructed epochs after ICA.
│22:51:02│ ⏳️ sub-17 Adding ICA to report.
│22:51:03│ ⏳️ sub-16 Adding config and sys info to report
│22:51:03│ ⏳️ sub-16 Saving report: ]8;id=302063;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=623299;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=923555;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\(]8;;\]8;id=722651;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=923555;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\)]8;;\]8;id=302063;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/]8;;\]8;id=623299;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\sub-16_task-SocialMemoryCuing_report.html]8;;\
│22:51:03│ ⏳️ sub-18 Adding ICA to report.
│22:51:03│ ⏳️ sub-23 Input: sub-23_task-SocialMemoryCuing_epo.fif
│22:51:03│ ⏳️ sub-23 Output: sub-23_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:04│ ⏳️ sub-23 Rejecting ICs: 0, 1, 3, 5
│22:51:04│ ⏳️ sub-23 Saving reconstructed epochs after ICA.
│22:51:04│ ⏳️ sub-19 Adding ICA to report.
│22:51:06│ ⏳️ sub-18 Adding config and sys info to report
│22:51:06│ ⏳️ sub-18 Saving report: ]8;id=32374;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=6097;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=14879;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\(]8;;\]8;id=487366;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=14879;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\)]8;;\]8;id=32374;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/]8;;\]8;id=6097;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\sub-18_task-SocialMemoryCuing_report.html]8;;\
│22:51:07│ ⏳️ sub-24 Input: sub-24_task-SocialMemoryCuing_epo.fif
│22:51:07│ ⏳️ sub-24 Output: sub-24_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:07│ ⏳️ sub-24 Rejecting ICs: 0, 2, 8, 10
│22:51:07│ ⏳️ sub-24 Saving reconstructed epochs after ICA.
│22:51:07│ ⏳️ sub-21 Adding ICA to report.
│22:51:07│ ⏳️ sub-22 Adding ICA to report.
│22:51:07│ ⏳️ sub-17 Adding config and sys info to report
│22:51:07│ ⏳️ sub-17 Saving report: ]8;id=436720;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=202988;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=365281;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\(]8;;\]8;id=635143;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=365281;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\)]8;;\]8;id=436720;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/]8;;\]8;id=202988;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\sub-17_task-SocialMemoryCuing_report.html]8;;\
│22:51:08│ ⏳️ sub-25 Input: sub-25_task-SocialMemoryCuing_epo.fif
│22:51:08│ ⏳️ sub-25 Output: sub-25_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:08│ ⏳️ sub-25 Rejecting ICs: 0, 1
│22:51:08│ ⏳️ sub-25 Saving reconstructed epochs after ICA.
│22:51:09│ ⏳️ sub-19 Adding config and sys info to report
│22:51:09│ ⏳️ sub-19 Saving report: ]8;id=334128;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=402101;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=663610;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\(]8;;\]8;id=30441;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=663610;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\)]8;;\]8;id=334128;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/]8;;\]8;id=402101;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\sub-19_task-SocialMemoryCuing_report.html]8;;\
│22:51:09│ ⏳️ sub-26 Input: sub-26_task-SocialMemoryCuing_epo.fif
│22:51:09│ ⏳️ sub-26 Output: sub-26_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:09│ ⏳️ sub-23 Adding ICA to report.
│22:51:09│ ⏳️ sub-26 Rejecting ICs: 0, 1, 2, 5, 7, 9
│22:51:09│ ⏳️ sub-26 Saving reconstructed epochs after ICA.
│22:51:11│ ⏳️ sub-25 Adding ICA to report.
│22:51:12│ ⏳️ sub-24 Adding ICA to report.
│22:51:12│ ⏳️ sub-21 Adding config and sys info to report
│22:51:12│ ⏳️ sub-21 Saving report: ]8;id=760835;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=818683;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=567966;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\(]8;;\]8;id=491801;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=567966;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\)]8;;\]8;id=760835;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/]8;;\]8;id=818683;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\sub-21_task-SocialMemoryCuing_report.html]8;;\
│22:51:13│ ⏳️ sub-27 Input: sub-27_task-SocialMemoryCuing_epo.fif
│22:51:13│ ⏳️ sub-27 Output: sub-27_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:13│ ⏳️ sub-22 Adding config and sys info to report
│22:51:13│ ⏳️ sub-22 Saving report: ]8;id=172528;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=223621;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=283724;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\(]8;;\]8;id=865298;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=283724;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\)]8;;\]8;id=172528;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/]8;;\]8;id=223621;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\sub-22_task-SocialMemoryCuing_report.html]8;;\
│22:51:13│ ⏳️ sub-27 Rejecting ICs: 0, 2, 6, 7, 9, 10
│22:51:13│ ⏳️ sub-28 Input: sub-28_task-SocialMemoryCuing_epo.fif
│22:51:13│ ⏳️ sub-28 Output: sub-28_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:13│ ⏳️ sub-27 Saving reconstructed epochs after ICA.
│22:51:13│ ⏳️ sub-28 Rejecting ICs: 0, 3, 4, 13, 20, 21, 23
│22:51:13│ ⏳️ sub-28 Saving reconstructed epochs after ICA.
│22:51:14│ ⏳️ sub-23 Adding config and sys info to report
│22:51:14│ ⏳️ sub-23 Saving report: ]8;id=73738;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=353356;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=432238;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\(]8;;\]8;id=752137;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=432238;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\)]8;;\]8;id=73738;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/]8;;\]8;id=353356;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\sub-23_task-SocialMemoryCuing_report.html]8;;\
│22:51:14│ ⏳️ sub-30 Input: sub-30_task-SocialMemoryCuing_epo.fif
│22:51:14│ ⏳️ sub-30 Output: sub-30_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:14│ ⏳️ sub-25 Adding config and sys info to report
│22:51:14│ ⏳️ sub-30 Rejecting ICs: 0, 2
│22:51:14│ ⏳️ sub-25 Saving report: ]8;id=587376;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=691439;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=204763;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\(]8;;\]8;id=966969;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=204763;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\)]8;;\]8;id=587376;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/]8;;\]8;id=691439;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\sub-25_task-SocialMemoryCuing_report.html]8;;\
│22:51:15│ ⏳️ sub-32 Input: sub-32_task-SocialMemoryCuing_epo.fif
│22:51:15│ ⏳️ sub-32 Output: sub-32_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:15│ ⏳️ sub-30 Saving reconstructed epochs after ICA.
│22:51:15│ ⏳️ sub-32 Rejecting ICs: 0, 1, 2, 9
│22:51:15│ ⏳️ sub-32 Saving reconstructed epochs after ICA.
│22:51:16│ ⏳️ sub-26 Adding ICA to report.
│22:51:17│ ⏳️ sub-24 Adding config and sys info to report
│22:51:17│ ⏳️ sub-24 Saving report: ]8;id=14363;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=323537;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=856045;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\(]8;;\]8;id=566775;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=856045;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\)]8;;\]8;id=14363;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/]8;;\]8;id=323537;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\sub-24_task-SocialMemoryCuing_report.html]8;;\
│22:51:17│ ⏳️ sub-33 Input: sub-33_task-SocialMemoryCuing_epo.fif
│22:51:18│ ⏳️ sub-33 Output: sub-33_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:18│ ⏳️ sub-33 Rejecting ICs: 0, 1, 4, 7
│22:51:18│ ⏳️ sub-33 Saving reconstructed epochs after ICA.
│22:51:18│ ⏳️ sub-30 Adding ICA to report.
│22:51:20│ ⏳️ sub-32 Adding ICA to report.
│22:51:21│ ⏳️ sub-27 Adding ICA to report.
│22:51:22│ ⏳️ sub-30 Adding config and sys info to report
│22:51:22│ ⏳️ sub-30 Saving report: ]8;id=196482;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=399321;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=148761;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\(]8;;\]8;id=523661;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=148761;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\)]8;;\]8;id=196482;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/]8;;\]8;id=399321;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\sub-30_task-SocialMemoryCuing_report.html]8;;\
│22:51:22│ ⏳️ sub-34 Input: sub-34_task-SocialMemoryCuing_epo.fif
│22:51:22│ ⏳️ sub-34 Output: sub-34_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:22│ ⏳️ sub-34 Rejecting ICs: 0, 1, 2, 3, 7, 8, 9, 10
│22:51:22│ ⏳️ sub-34 Saving reconstructed epochs after ICA.
│22:51:23│ ⏳️ sub-28 Adding ICA to report.
│22:51:23│ ⏳️ sub-33 Adding ICA to report.
│22:51:24│ ⏳️ sub-26 Adding config and sys info to report
│22:51:24│ ⏳️ sub-26 Saving report: ]8;id=689751;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=313316;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=548032;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\(]8;;\]8;id=932976;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=548032;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\)]8;;\]8;id=689751;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/]8;;\]8;id=313316;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\sub-26_task-SocialMemoryCuing_report.html]8;;\
│22:51:24│ ⏳️ sub-35 Input: sub-35_task-SocialMemoryCuing_epo.fif
│22:51:24│ ⏳️ sub-35 Output: sub-35_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:24│ ⏳️ sub-35 Rejecting ICs: 0, 1
│22:51:24│ ⏳️ sub-35 Saving reconstructed epochs after ICA.
│22:51:25│ ⏳️ sub-32 Adding config and sys info to report
│22:51:25│ ⏳️ sub-32 Saving report: ]8;id=649849;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=902742;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=241856;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\(]8;;\]8;id=49606;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=241856;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\)]8;;\]8;id=649849;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/]8;;\]8;id=902742;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\sub-32_task-SocialMemoryCuing_report.html]8;;\
│22:51:25│ ⏳️ sub-38 Input: sub-38_task-SocialMemoryCuing_epo.fif
│22:51:25│ ⏳️ sub-38 Output: sub-38_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:26│ ⏳️ sub-38 Rejecting ICs: 0, 1
│22:51:26│ ⏳️ sub-38 Saving reconstructed epochs after ICA.
│22:51:28│ ⏳️ sub-35 Adding ICA to report.
│22:51:28│ ⏳️ sub-27 Adding config and sys info to report
│22:51:28│ ⏳️ sub-27 Saving report: ]8;id=317657;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=144390;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=349473;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\(]8;;\]8;id=778762;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=349473;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\)]8;;\]8;id=317657;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/]8;;\]8;id=144390;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\sub-27_task-SocialMemoryCuing_report.html]8;;\
│22:51:28│ ⏳️ sub-33 Adding config and sys info to report
│22:51:28│ ⏳️ sub-33 Saving report: ]8;id=87757;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=518300;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=329237;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\(]8;;\]8;id=321715;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=329237;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\)]8;;\]8;id=87757;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/]8;;\]8;id=518300;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\sub-33_task-SocialMemoryCuing_report.html]8;;\
│22:51:28│ ⏳️ sub-39 Input: sub-39_task-SocialMemoryCuing_epo.fif
│22:51:28│ ⏳️ sub-39 Output: sub-39_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:28│ ⏳️ sub-40 Input: sub-40_task-SocialMemoryCuing_epo.fif
│22:51:28│ ⏳️ sub-40 Output: sub-40_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:29│ ⏳️ sub-39 Rejecting ICs: 0, 1, 2, 6, 7
│22:51:29│ ⏳️ sub-40 Rejecting ICs: 0, 1
│22:51:29│ ⏳️ sub-39 Saving reconstructed epochs after ICA.
│22:51:29│ ⏳️ sub-40 Saving reconstructed epochs after ICA.
│22:51:29│ ⏳️ sub-38 Adding ICA to report.
│22:51:31│ ⏳️ sub-34 Adding ICA to report.
│22:51:31│ ⏳️ sub-28 Adding config and sys info to report
│22:51:31│ ⏳️ sub-28 Saving report: ]8;id=670903;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=898;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=36800;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\(]8;;\]8;id=681282;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=36800;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\)]8;;\]8;id=670903;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/]8;;\]8;id=898;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\sub-28_task-SocialMemoryCuing_report.html]8;;\
│22:51:31│ ⏳️ sub-35 Adding config and sys info to report
│22:51:31│ ⏳️ sub-35 Saving report: ]8;id=901231;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=118513;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=208494;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\(]8;;\]8;id=885095;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=208494;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\)]8;;\]8;id=901231;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/]8;;\]8;id=118513;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\sub-35_task-SocialMemoryCuing_report.html]8;;\
│22:51:31│ ⏳️ sub-43 Input: sub-43_task-SocialMemoryCuing_epo.fif
│22:51:31│ ⏳️ sub-41 Input: sub-41_task-SocialMemoryCuing_epo.fif
│22:51:31│ ⏳️ sub-41 Output: sub-41_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:31│ ⏳️ sub-43 Output: sub-43_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:31│ ⏳️ sub-43 Rejecting ICs: 0, 1
│22:51:31│ ⏳️ sub-41 Rejecting ICs: 0, 1, 8, 11, 12
│22:51:32│ ⏳️ sub-38 Adding config and sys info to report
│22:51:32│ ⏳️ sub-43 Saving reconstructed epochs after ICA.
│22:51:32│ ⏳️ sub-41 Saving reconstructed epochs after ICA.
│22:51:32│ ⏳️ sub-38 Saving report: ]8;id=128772;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=988837;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=216674;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\(]8;;\]8;id=665593;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=216674;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\)]8;;\]8;id=128772;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/]8;;\]8;id=988837;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\sub-38_task-SocialMemoryCuing_report.html]8;;\
│22:51:32│ ⏳️ sub-40 Adding ICA to report.
│22:51:32│ ⏳️ sub-44 Input: sub-44_task-SocialMemoryCuing_epo.fif
│22:51:32│ ⏳️ sub-44 Output: sub-44_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:32│ ⏳️ sub-44 Rejecting ICs: 0, 1, 2, 3, 4, 5, 6
│22:51:32│ ⏳️ sub-44 Saving reconstructed epochs after ICA.
│22:51:35│ ⏳️ sub-39 Adding ICA to report.
│22:51:35│ ⏳️ sub-43 Adding ICA to report.
│22:51:35│ ⏳️ sub-40 Adding config and sys info to report
│22:51:35│ ⏳️ sub-40 Saving report: ]8;id=752632;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=181718;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=743957;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\(]8;;\]8;id=189387;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=743957;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\)]8;;\]8;id=752632;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/]8;;\]8;id=181718;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\sub-40_task-SocialMemoryCuing_report.html]8;;\
│22:51:35│ ⏳️ sub-45 Input: sub-45_task-SocialMemoryCuing_epo.fif
│22:51:35│ ⏳️ sub-45 Output: sub-45_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:36│ ⏳️ sub-45 Rejecting ICs: 0, 1, 2, 5, 8, 9
│22:51:36│ ⏳️ sub-45 Saving reconstructed epochs after ICA.
│22:51:38│ ⏳️ sub-43 Adding config and sys info to report
│22:51:38│ ⏳️ sub-43 Saving report: ]8;id=719724;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=525905;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=60494;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\(]8;;\]8;id=146331;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=60494;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\)]8;;\]8;id=719724;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/]8;;\]8;id=525905;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\sub-43_task-SocialMemoryCuing_report.html]8;;\
│22:51:38│ ⏳️ sub-46 Input: sub-46_task-SocialMemoryCuing_epo.fif
│22:51:38│ ⏳️ sub-46 Output: sub-46_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:38│ ⏳️ sub-41 Adding ICA to report.
│22:51:38│ ⏳️ sub-46 Rejecting ICs: 0, 1
│22:51:38│ ⏳️ sub-46 Saving reconstructed epochs after ICA.
│22:51:40│ ⏳️ sub-44 Adding ICA to report.
│22:51:41│ ⏳️ sub-34 Adding config and sys info to report
│22:51:41│ ⏳️ sub-34 Saving report: ]8;id=606681;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=993079;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=221491;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\(]8;;\]8;id=759320;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=221491;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\)]8;;\]8;id=606681;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/]8;;\]8;id=993079;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\sub-34_task-SocialMemoryCuing_report.html]8;;\
│22:51:41│ ⏳️ sub-48 Input: sub-48_task-SocialMemoryCuing_epo.fif
│22:51:41│ ⏳️ sub-39 Adding config and sys info to report
│22:51:41│ ⏳️ sub-48 Output: sub-48_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:41│ ⏳️ sub-39 Saving report: ]8;id=17209;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=857813;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=129698;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\(]8;;\]8;id=797448;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=129698;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\)]8;;\]8;id=17209;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/]8;;\]8;id=857813;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\sub-39_task-SocialMemoryCuing_report.html]8;;\
│22:51:41│ ⏳️ sub-48 Rejecting ICs: 0, 1, 5, 6, 9
│22:51:41│ ⏳️ sub-49 Input: sub-49_task-SocialMemoryCuing_epo.fif
│22:51:41│ ⏳️ sub-49 Output: sub-49_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:41│ ⏳️ sub-48 Saving reconstructed epochs after ICA.
│22:51:41│ ⏳️ sub-49 Rejecting ICs: 0, 1
│22:51:41│ ⏳️ sub-49 Saving reconstructed epochs after ICA.
│22:51:41│ ⏳️ sub-46 Adding ICA to report.
│22:51:44│ ⏳️ sub-45 Adding ICA to report.
│22:51:44│ ⏳️ sub-41 Adding config and sys info to report
│22:51:44│ ⏳️ sub-41 Saving report: ]8;id=771252;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=718775;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=381245;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\(]8;;\]8;id=61402;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=381245;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\)]8;;\]8;id=771252;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/]8;;\]8;id=718775;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\sub-41_task-SocialMemoryCuing_report.html]8;;\
│22:51:44│ ⏳️ sub-50 Input: sub-50_task-SocialMemoryCuing_epo.fif
│22:51:44│ ⏳️ sub-50 Output: sub-50_task-SocialMemoryCuing_proc-ica_epo.fif
│22:51:45│ ⏳️ sub-46 Adding config and sys info to report
│22:51:45│ ⏳️ sub-50 Rejecting ICs: 0, 1, 2, 4, 6, 7
│22:51:45│ ⏳️ sub-46 Saving report: ]8;id=115940;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=533315;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=912933;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\(]8;;\]8;id=856217;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=912933;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\)]8;;\]8;id=115940;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/]8;;\]8;id=533315;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\sub-46_task-SocialMemoryCuing_report.html]8;;\
│22:51:45│ ⏳️ sub-49 Adding ICA to report.
│22:51:45│ ⏳️ sub-50 Saving reconstructed epochs after ICA.
│22:51:47│ ⏳️ sub-48 Adding ICA to report.
│22:51:48│ ⏳️ sub-49 Adding config and sys info to report
│22:51:48│ ⏳️ sub-49 Saving report: ]8;id=927960;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=428348;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=947231;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\(]8;;\]8;id=212767;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=947231;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\)]8;;\]8;id=927960;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/]8;;\]8;id=428348;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\sub-49_task-SocialMemoryCuing_report.html]8;;\
│22:51:48│ ⏳️ sub-44 Adding config and sys info to report
│22:51:48│ ⏳️ sub-44 Saving report: ]8;id=715095;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=824608;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=124355;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\(]8;;\]8;id=261667;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=124355;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\)]8;;\]8;id=715095;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/]8;;\]8;id=824608;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\sub-44_task-SocialMemoryCuing_report.html]8;;\
│22:51:51│ ⏳️ sub-45 Adding config and sys info to report
│22:51:51│ ⏳️ sub-45 Saving report: ]8;id=64011;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=92350;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=354780;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\(]8;;\]8;id=677578;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=354780;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\)]8;;\]8;id=64011;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/]8;;\]8;id=92350;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\sub-45_task-SocialMemoryCuing_report.html]8;;\
│22:51:52│ ⏳️ sub-50 Adding ICA to report.
│22:51:53│ ⏳️ sub-48 Adding config and sys info to report
│22:51:53│ ⏳️ sub-48 Saving report: ]8;id=836057;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=902037;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=460856;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\(]8;;\]8;id=562565;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=460856;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\)]8;;\]8;id=836057;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/]8;;\]8;id=902037;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\sub-48_task-SocialMemoryCuing_report.html]8;;\
│22:51:58│ ⏳️ sub-50 Adding config and sys info to report
│22:51:58│ ⏳️ sub-50 Saving report: ]8;id=146828;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=477329;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=560583;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\(]8;;\]8;id=938871;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=560583;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\)]8;;\]8;id=146828;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/]8;;\]8;id=477329;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\sub-50_task-SocialMemoryCuing_report.html]8;;\
└────────┴ done (1m 26s)
In [71]:
# checkup: plot original (conventionally filtered) epochs
curr_checkup_epochs = mne.read_epochs(f"{curr_subject_path}/sub-01_task-SocialMemoryCuing_epo.fif")
mne.viz.plot_epochs_image(curr_checkup_epochs)
print("checkup: original (top) vs. ica-applied (bottom) epochs")
No description has been provided for this image 
checkup: original (top) vs. ica-applied (bottom) epochs
In [72]:
# checkup: plot ICA-corrected epochs
curr_checkup_epochs_ica = mne.read_epochs(f"{curr_subject_path}/sub-01_task-SocialMemoryCuing_proc-ica_epo.fif")
mne.viz.plot_epochs_image(curr_checkup_epochs_ica)
print("checkup: original (top) vs. ica-applied (bottom) epochs; Compare the scale in μV.")
No description has been provided for this image 
checkup: original (top) vs. ica-applied (bottom) epochs; Compare the scale in μV.

This checkup plot comparison shows less low frequency power in the average signal, and lower peak amplitudes of about 100 μV instead of about 160 μV in the original epochs plot. Combined with the less random absolute amplitude of the average signal, this indicates that by applying the ICA, some noise reduction was performed.

Pre-processing: Peak to Peak Rejection¶

The last step in the pre-processing is the peak to peak rejection (PTP). This also is followed by plots comparing the original epoch signals after basic filtering to the ICA and PTP filtered epoch signals.

In [36]:
curr_steps = "preprocessing/_08_ptp_reject"
if curr_steps in STEPS_TO_RUN and STEPS_TO_RUN[curr_steps]:
    !mne_bids_pipeline --config {config_path} --steps {curr_steps}

┌────────┬ Welcome aboard MNE-BIDS-Pipeline! 👋 ────────────────────────────────
│22:52:02│ 📝 Using configuration: ./mne-bids/config/mne-bids-pipeline.py
└────────┴ 
┌────────┬ init/_01_init_derivatives_dir ───────────────────────────────────────
│22:52:02│ ✅ Output directories already exist …
└────────┴ done (1s)
┌────────┬ init/_02_find_empty_room ────────────────────────────────────────────
│22:52:02│ ⏩ Skipping, empty-room data only relevant for MEG …
└────────┴ done (1s)
┌────────┬ preprocessing/_08_ptp_reject ────────────────────────────────────────
│22:52:02│ ⏳️ sub-01 Input:  sub-01_task-SocialMemoryCuing_proc-ica_epo.fif
│22:52:02│ ⏳️ sub-01 Output: sub-01_task-SocialMemoryCuing_proc-clean_epo.fif
│22:52:02│ ⏳️ sub-01 Generating rejection thresholds using autoreject …
│22:52:06│ ⏳️ sub-01 Using PTP rejection thresholds: {'eeg': 0.0001316722246434394}
│22:52:06│ ⏳️ sub-01 Adding cleaned epochs to report.
│22:52:08│ ⏳️ sub-01 Adding config and sys info to report
│22:52:10│ ⏳️ sub-01 Saving report: ]8;id=567561;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=956599;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=848676;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\(]8;;\]8;id=951511;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=848676;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\)]8;;\]8;id=567561;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/]8;;\]8;id=956599;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_report.html\sub-01_task-SocialMemoryCuing_report.html]8;;\
│22:52:10│ ⏳️ sub-02 Input:  sub-02_task-SocialMemoryCuing_proc-ica_epo.fif
│22:52:10│ ⏳️ sub-02 Output: sub-02_task-SocialMemoryCuing_proc-clean_epo.fif
│22:52:10│ ⏳️ sub-02 Generating rejection thresholds using autoreject …
│22:52:12│ ⏳️ sub-02 Using PTP rejection thresholds: {'eeg': 0.00013735470806736712}
│22:52:12│ ⏳️ sub-02 Adding cleaned epochs to report.
│22:52:14│ ⏳️ sub-02 Adding config and sys info to report
│22:52:14│ ⏳️ sub-02 Saving report: ]8;id=744831;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=759452;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=744437;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\(]8;;\]8;id=859785;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=744437;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\)]8;;\]8;id=744831;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/]8;;\]8;id=759452;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-02/eeg/sub-02_task-SocialMemoryCuing_report.html\sub-02_task-SocialMemoryCuing_report.html]8;;\
│22:52:14│ ⏳️ sub-03 Input:  sub-03_task-SocialMemoryCuing_proc-ica_epo.fif
│22:52:14│ ⏳️ sub-03 Output: sub-03_task-SocialMemoryCuing_proc-clean_epo.fif
│22:52:14│ ⏳️ sub-03 Generating rejection thresholds using autoreject …
│22:52:16│ ⏳️ sub-03 Using PTP rejection thresholds: {'eeg': 0.00021052467114409125}
│22:52:16│ ⏳️ sub-03 Adding cleaned epochs to report.
│22:52:18│ ⏳️ sub-03 Adding config and sys info to report
│22:52:18│ ⏳️ sub-03 Saving report: ]8;id=640758;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=897178;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=75551;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\(]8;;\]8;id=178560;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=75551;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\)]8;;\]8;id=640758;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/]8;;\]8;id=897178;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-03/eeg/sub-03_task-SocialMemoryCuing_report.html\sub-03_task-SocialMemoryCuing_report.html]8;;\
│22:52:18│ ⏳️ sub-04 Input:  sub-04_task-SocialMemoryCuing_proc-ica_epo.fif
│22:52:18│ ⏳️ sub-04 Output: sub-04_task-SocialMemoryCuing_proc-clean_epo.fif
│22:52:18│ ⏳️ sub-04 Generating rejection thresholds using autoreject …
│22:52:20│ ⏳️ sub-04 Using PTP rejection thresholds: {'eeg': 0.00010211401439741949}
│22:52:20│ ⏳️ sub-04 Adding cleaned epochs to report.
│22:52:22│ ⏳️ sub-04 Adding config and sys info to report
│22:52:22│ ⏳️ sub-04 Saving report: ]8;id=270310;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=374239;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=388926;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\(]8;;\]8;id=485521;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=388926;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\)]8;;\]8;id=270310;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/]8;;\]8;id=374239;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-04/eeg/sub-04_task-SocialMemoryCuing_report.html\sub-04_task-SocialMemoryCuing_report.html]8;;\
│22:52:22│ ⏳️ sub-06 Input:  sub-06_task-SocialMemoryCuing_proc-ica_epo.fif
│22:52:22│ ⏳️ sub-06 Output: sub-06_task-SocialMemoryCuing_proc-clean_epo.fif
│22:52:22│ ⏳️ sub-06 Generating rejection thresholds using autoreject …
│22:52:24│ ⏳️ sub-06 Using PTP rejection thresholds: {'eeg': 0.00010756448159058316}
│22:52:24│ ⏳️ sub-06 Adding cleaned epochs to report.
│22:52:26│ ⏳️ sub-06 Adding config and sys info to report
│22:52:26│ ⏳️ sub-06 Saving report: ]8;id=510124;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=935470;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=962481;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\(]8;;\]8;id=731693;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=962481;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\)]8;;\]8;id=510124;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/]8;;\]8;id=935470;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-06/eeg/sub-06_task-SocialMemoryCuing_report.html\sub-06_task-SocialMemoryCuing_report.html]8;;\
│22:52:26│ ⏳️ sub-07 Input:  sub-07_task-SocialMemoryCuing_proc-ica_epo.fif
│22:52:26│ ⏳️ sub-07 Output: sub-07_task-SocialMemoryCuing_proc-clean_epo.fif
│22:52:26│ ⏳️ sub-07 Generating rejection thresholds using autoreject …
│22:52:28│ ⏳️ sub-07 Using PTP rejection thresholds: {'eeg': 0.00018951656014674011}
│22:52:28│ ⏳️ sub-07 Adding cleaned epochs to report.
│22:52:30│ ⏳️ sub-07 Adding config and sys info to report
│22:52:30│ ⏳️ sub-07 Saving report: ]8;id=717339;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=567921;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=860043;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\(]8;;\]8;id=174011;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=860043;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\)]8;;\]8;id=717339;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/]8;;\]8;id=567921;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-07/eeg/sub-07_task-SocialMemoryCuing_report.html\sub-07_task-SocialMemoryCuing_report.html]8;;\
│22:52:30│ ⏳️ sub-09 Input:  sub-09_task-SocialMemoryCuing_proc-ica_epo.fif
│22:52:30│ ⏳️ sub-09 Output: sub-09_task-SocialMemoryCuing_proc-clean_epo.fif
│22:52:30│ ⏳️ sub-09 Generating rejection thresholds using autoreject …
│22:52:32│ ⏳️ sub-09 Using PTP rejection thresholds: {'eeg': 0.0002560289146435213}
│22:52:32│ ⏳️ sub-09 Adding cleaned epochs to report.
│22:52:33│ ⏳️ sub-09 Adding config and sys info to report
│22:52:33│ ⏳️ sub-09 Saving report: ]8;id=608075;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-09/eeg/sub-09_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=233490;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-09/eeg/sub-09_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=457568;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-09/eeg/sub-09_task-SocialMemoryCuing_report.html\(]8;;\]8;id=584296;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-09/eeg/sub-09_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=457568;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-09/eeg/sub-09_task-SocialMemoryCuing_report.html\)]8;;\]8;id=608075;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-09/eeg/sub-09_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-09/eeg/]8;;\]8;id=233490;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-09/eeg/sub-09_task-SocialMemoryCuing_report.html\sub-09_task-SocialMemoryCuing_report.html]8;;\
│22:52:34│ ⏳️ sub-10 Input:  sub-10_task-SocialMemoryCuing_proc-ica_epo.fif
│22:52:34│ ⏳️ sub-10 Output: sub-10_task-SocialMemoryCuing_proc-clean_epo.fif
│22:52:34│ ⏳️ sub-10 Generating rejection thresholds using autoreject …
│22:52:36│ ⏳️ sub-10 Using PTP rejection thresholds: {'eeg': 0.00017312688232317715}
│22:52:36│ ⏳️ sub-10 Adding cleaned epochs to report.
│22:52:38│ ⏳️ sub-10 Adding config and sys info to report
│22:52:38│ ⏳️ sub-10 Saving report: ]8;id=692719;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=807040;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=48227;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\(]8;;\]8;id=155086;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=48227;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\)]8;;\]8;id=692719;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/]8;;\]8;id=807040;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-10/eeg/sub-10_task-SocialMemoryCuing_report.html\sub-10_task-SocialMemoryCuing_report.html]8;;\
│22:52:38│ ⏳️ sub-11 Input:  sub-11_task-SocialMemoryCuing_proc-ica_epo.fif
│22:52:38│ ⏳️ sub-11 Output: sub-11_task-SocialMemoryCuing_proc-clean_epo.fif
│22:52:38│ ⏳️ sub-11 Generating rejection thresholds using autoreject …
│22:52:40│ ⏳️ sub-11 Using PTP rejection thresholds: {'eeg': 0.00026415173020395634}
│22:52:40│ ⏳️ sub-11 Adding cleaned epochs to report.
│22:52:42│ ⏳️ sub-11 Adding config and sys info to report
│22:52:42│ ⏳️ sub-11 Saving report: ]8;id=238698;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=298153;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=148674;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\(]8;;\]8;id=537162;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=148674;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\)]8;;\]8;id=238698;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/]8;;\]8;id=298153;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-11/eeg/sub-11_task-SocialMemoryCuing_report.html\sub-11_task-SocialMemoryCuing_report.html]8;;\
│22:52:42│ ⏳️ sub-12 Input:  sub-12_task-SocialMemoryCuing_proc-ica_epo.fif
│22:52:42│ ⏳️ sub-12 Output: sub-12_task-SocialMemoryCuing_proc-clean_epo.fif
│22:52:42│ ⏳️ sub-12 Generating rejection thresholds using autoreject …
│22:52:44│ ⏳️ sub-12 Adjusting PTP rejection threshold proposed by autoreject, as it is greater than ica_reject: eeg: 0.000668824667055589 -> 0.0004
│22:52:44│ ⏳️ sub-12 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:52:44│ ⏳️ sub-12 Adding cleaned epochs to report.
│22:52:46│ ⏳️ sub-12 Adding config and sys info to report
│22:52:46│ ⏳️ sub-12 Saving report: ]8;id=587886;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=654991;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=760478;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\(]8;;\]8;id=764653;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=760478;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\)]8;;\]8;id=587886;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/]8;;\]8;id=654991;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-12/eeg/sub-12_task-SocialMemoryCuing_report.html\sub-12_task-SocialMemoryCuing_report.html]8;;\
│22:52:46│ ⏳️ sub-13 Input:  sub-13_task-SocialMemoryCuing_proc-ica_epo.fif
│22:52:46│ ⏳️ sub-13 Output: sub-13_task-SocialMemoryCuing_proc-clean_epo.fif
│22:52:46│ ⏳️ sub-13 Generating rejection thresholds using autoreject …
│22:52:48│ ⏳️ sub-13 Using PTP rejection thresholds: {'eeg': 0.00021523352575555363}
│22:52:48│ ⏳️ sub-13 Adding cleaned epochs to report.
│22:52:50│ ⏳️ sub-13 Adding config and sys info to report
│22:52:50│ ⏳️ sub-13 Saving report: ]8;id=749153;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=487329;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=10398;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\(]8;;\]8;id=339309;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=10398;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\)]8;;\]8;id=749153;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/]8;;\]8;id=487329;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-13/eeg/sub-13_task-SocialMemoryCuing_report.html\sub-13_task-SocialMemoryCuing_report.html]8;;\
│22:52:50│ ⏳️ sub-14 Input:  sub-14_task-SocialMemoryCuing_proc-ica_epo.fif
│22:52:50│ ⏳️ sub-14 Output: sub-14_task-SocialMemoryCuing_proc-clean_epo.fif
│22:52:50│ ⏳️ sub-14 Generating rejection thresholds using autoreject …
│22:52:52│ ⏳️ sub-14 Using PTP rejection thresholds: {'eeg': 0.00011551099002849425}
│22:52:52│ ⏳️ sub-14 Adding cleaned epochs to report.
│22:52:54│ ⏳️ sub-14 Adding config and sys info to report
│22:52:54│ ⏳️ sub-14 Saving report: ]8;id=738999;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=797167;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=600316;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\(]8;;\]8;id=861762;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=600316;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\)]8;;\]8;id=738999;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/]8;;\]8;id=797167;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-14/eeg/sub-14_task-SocialMemoryCuing_report.html\sub-14_task-SocialMemoryCuing_report.html]8;;\
│22:52:54│ ⏳️ sub-15 Input:  sub-15_task-SocialMemoryCuing_proc-ica_epo.fif
│22:52:54│ ⏳️ sub-15 Output: sub-15_task-SocialMemoryCuing_proc-clean_epo.fif
│22:52:54│ ⏳️ sub-15 Generating rejection thresholds using autoreject …
│22:52:56│ ⏳️ sub-15 Adjusting PTP rejection threshold proposed by autoreject, as it is greater than ica_reject: eeg: 0.0004991183059332113 -> 0.0004
│22:52:56│ ⏳️ sub-15 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:52:57│ ⏳️ sub-15 Adding cleaned epochs to report.
│22:52:58│ ⏳️ sub-15 Adding config and sys info to report
│22:52:58│ ⏳️ sub-15 Saving report: ]8;id=105495;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=559489;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=208779;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\(]8;;\]8;id=227420;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=208779;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\)]8;;\]8;id=105495;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/]8;;\]8;id=559489;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-15/eeg/sub-15_task-SocialMemoryCuing_report.html\sub-15_task-SocialMemoryCuing_report.html]8;;\
│22:52:58│ ⏳️ sub-16 Input:  sub-16_task-SocialMemoryCuing_proc-ica_epo.fif
│22:52:58│ ⏳️ sub-16 Output: sub-16_task-SocialMemoryCuing_proc-clean_epo.fif
│22:52:58│ ⏳️ sub-16 Generating rejection thresholds using autoreject …
│22:53:01│ ⏳️ sub-16 Using PTP rejection thresholds: {'eeg': 0.0001768642225204885}
│22:53:01│ ⏳️ sub-16 Adding cleaned epochs to report.
│22:53:02│ ⏳️ sub-16 Adding config and sys info to report
│22:53:02│ ⏳️ sub-16 Saving report: ]8;id=443739;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=920550;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=414086;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\(]8;;\]8;id=74941;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=414086;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\)]8;;\]8;id=443739;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/]8;;\]8;id=920550;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-16/eeg/sub-16_task-SocialMemoryCuing_report.html\sub-16_task-SocialMemoryCuing_report.html]8;;\
│22:53:02│ ⏳️ sub-17 Input:  sub-17_task-SocialMemoryCuing_proc-ica_epo.fif
│22:53:02│ ⏳️ sub-17 Output: sub-17_task-SocialMemoryCuing_proc-clean_epo.fif
│22:53:03│ ⏳️ sub-17 Generating rejection thresholds using autoreject …
│22:53:05│ ⏳️ sub-17 Using PTP rejection thresholds: {'eeg': 0.00012571946048715578}
│22:53:05│ ⏳️ sub-17 Adding cleaned epochs to report.
│22:53:06│ ⏳️ sub-17 Adding config and sys info to report
│22:53:06│ ⏳️ sub-17 Saving report: ]8;id=247504;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=645789;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=375172;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\(]8;;\]8;id=279426;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=375172;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\)]8;;\]8;id=247504;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/]8;;\]8;id=645789;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-17/eeg/sub-17_task-SocialMemoryCuing_report.html\sub-17_task-SocialMemoryCuing_report.html]8;;\
│22:53:06│ ⏳️ sub-18 Input:  sub-18_task-SocialMemoryCuing_proc-ica_epo.fif
│22:53:06│ ⏳️ sub-18 Output: sub-18_task-SocialMemoryCuing_proc-clean_epo.fif
│22:53:07│ ⏳️ sub-18 Generating rejection thresholds using autoreject …
│22:53:09│ ⏳️ sub-18 Using PTP rejection thresholds: {'eeg': 0.00026071984810941437}
│22:53:09│ ⏳️ sub-18 Adding cleaned epochs to report.
│22:53:10│ ⏳️ sub-18 Adding config and sys info to report
│22:53:10│ ⏳️ sub-18 Saving report: ]8;id=572116;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=434027;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=276915;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\(]8;;\]8;id=719443;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=276915;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\)]8;;\]8;id=572116;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/]8;;\]8;id=434027;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-18/eeg/sub-18_task-SocialMemoryCuing_report.html\sub-18_task-SocialMemoryCuing_report.html]8;;\
│22:53:10│ ⏳️ sub-19 Input:  sub-19_task-SocialMemoryCuing_proc-ica_epo.fif
│22:53:10│ ⏳️ sub-19 Output: sub-19_task-SocialMemoryCuing_proc-clean_epo.fif
│22:53:11│ ⏳️ sub-19 Generating rejection thresholds using autoreject …
│22:53:13│ ⏳️ sub-19 Using PTP rejection thresholds: {'eeg': 0.0003135990649295331}
│22:53:13│ ⏳️ sub-19 Adding cleaned epochs to report.
│22:53:15│ ⏳️ sub-19 Adding config and sys info to report
│22:53:15│ ⏳️ sub-19 Saving report: ]8;id=687430;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=477996;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=852289;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\(]8;;\]8;id=754861;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=852289;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\)]8;;\]8;id=687430;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/]8;;\]8;id=477996;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-19/eeg/sub-19_task-SocialMemoryCuing_report.html\sub-19_task-SocialMemoryCuing_report.html]8;;\
│22:53:15│ ⏳️ sub-21 Input:  sub-21_task-SocialMemoryCuing_proc-ica_epo.fif
│22:53:15│ ⏳️ sub-21 Output: sub-21_task-SocialMemoryCuing_proc-clean_epo.fif
│22:53:15│ ⏳️ sub-21 Generating rejection thresholds using autoreject …
│22:53:17│ ⏳️ sub-21 Using PTP rejection thresholds: {'eeg': 0.00023404638347461376}
│22:53:17│ ⏳️ sub-21 Adding cleaned epochs to report.
│22:53:19│ ⏳️ sub-21 Adding config and sys info to report
│22:53:19│ ⏳️ sub-21 Saving report: ]8;id=453906;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=805231;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=787155;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\(]8;;\]8;id=382096;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=787155;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\)]8;;\]8;id=453906;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/]8;;\]8;id=805231;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-21/eeg/sub-21_task-SocialMemoryCuing_report.html\sub-21_task-SocialMemoryCuing_report.html]8;;\
│22:53:19│ ⏳️ sub-22 Input:  sub-22_task-SocialMemoryCuing_proc-ica_epo.fif
│22:53:19│ ⏳️ sub-22 Output: sub-22_task-SocialMemoryCuing_proc-clean_epo.fif
│22:53:19│ ⏳️ sub-22 Generating rejection thresholds using autoreject …
│22:53:21│ ⏳️ sub-22 Using PTP rejection thresholds: {'eeg': 0.00014836952886739083}
│22:53:21│ ⏳️ sub-22 Adding cleaned epochs to report.
│22:53:23│ ⏳️ sub-22 Adding config and sys info to report
│22:53:23│ ⏳️ sub-22 Saving report: ]8;id=74743;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=688336;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=22101;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\(]8;;\]8;id=987274;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=22101;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\)]8;;\]8;id=74743;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/]8;;\]8;id=688336;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-22/eeg/sub-22_task-SocialMemoryCuing_report.html\sub-22_task-SocialMemoryCuing_report.html]8;;\
│22:53:23│ ⏳️ sub-23 Input:  sub-23_task-SocialMemoryCuing_proc-ica_epo.fif
│22:53:23│ ⏳️ sub-23 Output: sub-23_task-SocialMemoryCuing_proc-clean_epo.fif
│22:53:23│ ⏳️ sub-23 Generating rejection thresholds using autoreject …
│22:53:25│ ⏳️ sub-23 Using PTP rejection thresholds: {'eeg': 0.00019064771765908885}
│22:53:25│ ⏳️ sub-23 Adding cleaned epochs to report.
│22:53:27│ ⏳️ sub-23 Adding config and sys info to report
│22:53:27│ ⏳️ sub-23 Saving report: ]8;id=625239;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=832960;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=390540;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\(]8;;\]8;id=498926;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=390540;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\)]8;;\]8;id=625239;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/]8;;\]8;id=832960;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-23/eeg/sub-23_task-SocialMemoryCuing_report.html\sub-23_task-SocialMemoryCuing_report.html]8;;\
│22:53:27│ ⏳️ sub-24 Input:  sub-24_task-SocialMemoryCuing_proc-ica_epo.fif
│22:53:27│ ⏳️ sub-24 Output: sub-24_task-SocialMemoryCuing_proc-clean_epo.fif
│22:53:27│ ⏳️ sub-24 Generating rejection thresholds using autoreject …
│22:53:29│ ⏳️ sub-24 Using PTP rejection thresholds: {'eeg': 0.000374401908707628}
│22:53:29│ ⏳️ sub-24 Adding cleaned epochs to report.
│22:53:31│ ⏳️ sub-24 Adding config and sys info to report
│22:53:31│ ⏳️ sub-24 Saving report: ]8;id=887289;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=366669;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=215303;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\(]8;;\]8;id=62926;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=215303;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\)]8;;\]8;id=887289;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/]8;;\]8;id=366669;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-24/eeg/sub-24_task-SocialMemoryCuing_report.html\sub-24_task-SocialMemoryCuing_report.html]8;;\
│22:53:31│ ⏳️ sub-25 Input:  sub-25_task-SocialMemoryCuing_proc-ica_epo.fif
│22:53:31│ ⏳️ sub-25 Output: sub-25_task-SocialMemoryCuing_proc-clean_epo.fif
│22:53:31│ ⏳️ sub-25 Generating rejection thresholds using autoreject …
│22:53:33│ ⏳️ sub-25 Using PTP rejection thresholds: {'eeg': 0.00011247028498793218}
│22:53:33│ ⏳️ sub-25 Adding cleaned epochs to report.
│22:53:35│ ⏳️ sub-25 Adding config and sys info to report
│22:53:35│ ⏳️ sub-25 Saving report: ]8;id=915226;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=895939;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=664947;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\(]8;;\]8;id=813403;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=664947;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\)]8;;\]8;id=915226;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/]8;;\]8;id=895939;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-25/eeg/sub-25_task-SocialMemoryCuing_report.html\sub-25_task-SocialMemoryCuing_report.html]8;;\
│22:53:35│ ⏳️ sub-26 Input:  sub-26_task-SocialMemoryCuing_proc-ica_epo.fif
│22:53:35│ ⏳️ sub-26 Output: sub-26_task-SocialMemoryCuing_proc-clean_epo.fif
│22:53:35│ ⏳️ sub-26 Generating rejection thresholds using autoreject …
│22:53:37│ ⏳️ sub-26 Using PTP rejection thresholds: {'eeg': 0.00016684468047359927}
│22:53:37│ ⏳️ sub-26 Adding cleaned epochs to report.
│22:53:39│ ⏳️ sub-26 Adding config and sys info to report
│22:53:39│ ⏳️ sub-26 Saving report: ]8;id=863956;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=566715;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=641969;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\(]8;;\]8;id=154501;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=641969;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\)]8;;\]8;id=863956;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/]8;;\]8;id=566715;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-26/eeg/sub-26_task-SocialMemoryCuing_report.html\sub-26_task-SocialMemoryCuing_report.html]8;;\
│22:53:39│ ⏳️ sub-27 Input:  sub-27_task-SocialMemoryCuing_proc-ica_epo.fif
│22:53:39│ ⏳️ sub-27 Output: sub-27_task-SocialMemoryCuing_proc-clean_epo.fif
│22:53:39│ ⏳️ sub-27 Generating rejection thresholds using autoreject …
│22:53:41│ ⏳️ sub-27 Using PTP rejection thresholds: {'eeg': 9.27268097083495e-05}
│22:53:42│ ⏳️ sub-27 Adding cleaned epochs to report.
│22:53:43│ ⏳️ sub-27 Adding config and sys info to report
│22:53:43│ ⏳️ sub-27 Saving report: ]8;id=472758;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=343440;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=358648;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\(]8;;\]8;id=346473;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=358648;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\)]8;;\]8;id=472758;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/]8;;\]8;id=343440;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-27/eeg/sub-27_task-SocialMemoryCuing_report.html\sub-27_task-SocialMemoryCuing_report.html]8;;\
│22:53:43│ ⏳️ sub-28 Input:  sub-28_task-SocialMemoryCuing_proc-ica_epo.fif
│22:53:43│ ⏳️ sub-28 Output: sub-28_task-SocialMemoryCuing_proc-clean_epo.fif
│22:53:44│ ⏳️ sub-28 Generating rejection thresholds using autoreject …
│22:53:46│ ⏳️ sub-28 Using PTP rejection thresholds: {'eeg': 0.0001462792917250353}
│22:53:46│ ⏳️ sub-28 Adding cleaned epochs to report.
│22:53:47│ ⏳️ sub-28 Adding config and sys info to report
│22:53:47│ ⏳️ sub-28 Saving report: ]8;id=693375;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=272485;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=968819;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\(]8;;\]8;id=489495;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=968819;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\)]8;;\]8;id=693375;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/]8;;\]8;id=272485;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-28/eeg/sub-28_task-SocialMemoryCuing_report.html\sub-28_task-SocialMemoryCuing_report.html]8;;\
│22:53:47│ ⏳️ sub-30 Input:  sub-30_task-SocialMemoryCuing_proc-ica_epo.fif
│22:53:47│ ⏳️ sub-30 Output: sub-30_task-SocialMemoryCuing_proc-clean_epo.fif
│22:53:48│ ⏳️ sub-30 Generating rejection thresholds using autoreject …
│22:53:50│ ⏳️ sub-30 Adjusting PTP rejection threshold proposed by autoreject, as it is greater than ica_reject: eeg: 0.00045154270191434293 -> 0.0004
│22:53:50│ ⏳️ sub-30 Using PTP rejection thresholds: {'eeg': 0.0004}
│22:53:50│ ⏳️ sub-30 Adding cleaned epochs to report.
│22:53:51│ ⏳️ sub-30 Adding config and sys info to report
│22:53:51│ ⏳️ sub-30 Saving report: ]8;id=740621;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=962799;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=30784;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\(]8;;\]8;id=886736;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=30784;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\)]8;;\]8;id=740621;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/]8;;\]8;id=962799;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-30/eeg/sub-30_task-SocialMemoryCuing_report.html\sub-30_task-SocialMemoryCuing_report.html]8;;\
│22:53:51│ ⏳️ sub-32 Input:  sub-32_task-SocialMemoryCuing_proc-ica_epo.fif
│22:53:51│ ⏳️ sub-32 Output: sub-32_task-SocialMemoryCuing_proc-clean_epo.fif
│22:53:52│ ⏳️ sub-32 Generating rejection thresholds using autoreject …
│22:53:54│ ⏳️ sub-32 Using PTP rejection thresholds: {'eeg': 0.00013498426673373324}
│22:53:54│ ⏳️ sub-32 Adding cleaned epochs to report.
│22:53:55│ ⏳️ sub-32 Adding config and sys info to report
│22:53:55│ ⏳️ sub-32 Saving report: ]8;id=724845;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=396486;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=749369;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\(]8;;\]8;id=294865;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=749369;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\)]8;;\]8;id=724845;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/]8;;\]8;id=396486;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-32/eeg/sub-32_task-SocialMemoryCuing_report.html\sub-32_task-SocialMemoryCuing_report.html]8;;\
│22:53:55│ ⏳️ sub-33 Input:  sub-33_task-SocialMemoryCuing_proc-ica_epo.fif
│22:53:55│ ⏳️ sub-33 Output: sub-33_task-SocialMemoryCuing_proc-clean_epo.fif
│22:53:56│ ⏳️ sub-33 Generating rejection thresholds using autoreject …
│22:53:58│ ⏳️ sub-33 Using PTP rejection thresholds: {'eeg': 7.00185822969009e-05}
│22:53:58│ ⏳️ sub-33 Adding cleaned epochs to report.
│22:54:00│ ⏳️ sub-33 Adding config and sys info to report
│22:54:00│ ⏳️ sub-33 Saving report: ]8;id=720901;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=772451;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=143577;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\(]8;;\]8;id=762618;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=143577;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\)]8;;\]8;id=720901;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/]8;;\]8;id=772451;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-33/eeg/sub-33_task-SocialMemoryCuing_report.html\sub-33_task-SocialMemoryCuing_report.html]8;;\
│22:54:00│ ⏳️ sub-34 Input:  sub-34_task-SocialMemoryCuing_proc-ica_epo.fif
│22:54:00│ ⏳️ sub-34 Output: sub-34_task-SocialMemoryCuing_proc-clean_epo.fif
│22:54:00│ ⏳️ sub-34 Generating rejection thresholds using autoreject …
│22:54:02│ ⏳️ sub-34 Using PTP rejection thresholds: {'eeg': 0.00013050411335881572}
│22:54:02│ ⏳️ sub-34 Adding cleaned epochs to report.
│22:54:04│ ⏳️ sub-34 Adding config and sys info to report
│22:54:04│ ⏳️ sub-34 Saving report: ]8;id=628128;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=893690;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=149786;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\(]8;;\]8;id=684741;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=149786;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\)]8;;\]8;id=628128;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/]8;;\]8;id=893690;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-34/eeg/sub-34_task-SocialMemoryCuing_report.html\sub-34_task-SocialMemoryCuing_report.html]8;;\
│22:54:04│ ⏳️ sub-35 Input:  sub-35_task-SocialMemoryCuing_proc-ica_epo.fif
│22:54:04│ ⏳️ sub-35 Output: sub-35_task-SocialMemoryCuing_proc-clean_epo.fif
│22:54:04│ ⏳️ sub-35 Generating rejection thresholds using autoreject …
│22:54:06│ ⏳️ sub-35 Using PTP rejection thresholds: {'eeg': 0.0003363324920424958}
│22:54:06│ ⏳️ sub-35 Adding cleaned epochs to report.
│22:54:08│ ⏳️ sub-35 Adding config and sys info to report
│22:54:08│ ⏳️ sub-35 Saving report: ]8;id=600509;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=217527;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=682077;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\(]8;;\]8;id=932124;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=682077;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\)]8;;\]8;id=600509;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/]8;;\]8;id=217527;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-35/eeg/sub-35_task-SocialMemoryCuing_report.html\sub-35_task-SocialMemoryCuing_report.html]8;;\
│22:54:08│ ⏳️ sub-38 Input:  sub-38_task-SocialMemoryCuing_proc-ica_epo.fif
│22:54:08│ ⏳️ sub-38 Output: sub-38_task-SocialMemoryCuing_proc-clean_epo.fif
│22:54:08│ ⏳️ sub-38 Generating rejection thresholds using autoreject …
│22:54:10│ ⏳️ sub-38 Using PTP rejection thresholds: {'eeg': 0.00016374118654997774}
│22:54:10│ ⏳️ sub-38 Adding cleaned epochs to report.
│22:54:12│ ⏳️ sub-38 Adding config and sys info to report
│22:54:12│ ⏳️ sub-38 Saving report: ]8;id=842360;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=178076;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=627275;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\(]8;;\]8;id=892159;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=627275;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\)]8;;\]8;id=842360;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/]8;;\]8;id=178076;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-38/eeg/sub-38_task-SocialMemoryCuing_report.html\sub-38_task-SocialMemoryCuing_report.html]8;;\
│22:54:12│ ⏳️ sub-39 Input:  sub-39_task-SocialMemoryCuing_proc-ica_epo.fif
│22:54:12│ ⏳️ sub-39 Output: sub-39_task-SocialMemoryCuing_proc-clean_epo.fif
│22:54:12│ ⏳️ sub-39 Generating rejection thresholds using autoreject …
│22:54:14│ ⏳️ sub-39 Using PTP rejection thresholds: {'eeg': 0.00012210028151345785}
│22:54:14│ ⏳️ sub-39 Adding cleaned epochs to report.
│22:54:16│ ⏳️ sub-39 Adding config and sys info to report
│22:54:16│ ⏳️ sub-39 Saving report: ]8;id=152898;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=311079;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=53520;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\(]8;;\]8;id=890345;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=53520;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\)]8;;\]8;id=152898;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/]8;;\]8;id=311079;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-39/eeg/sub-39_task-SocialMemoryCuing_report.html\sub-39_task-SocialMemoryCuing_report.html]8;;\
│22:54:16│ ⏳️ sub-40 Input:  sub-40_task-SocialMemoryCuing_proc-ica_epo.fif
│22:54:16│ ⏳️ sub-40 Output: sub-40_task-SocialMemoryCuing_proc-clean_epo.fif
│22:54:16│ ⏳️ sub-40 Generating rejection thresholds using autoreject …
│22:54:18│ ⏳️ sub-40 Using PTP rejection thresholds: {'eeg': 0.0002104365966639237}
│22:54:19│ ⏳️ sub-40 Adding cleaned epochs to report.
│22:54:20│ ⏳️ sub-40 Adding config and sys info to report
│22:54:20│ ⏳️ sub-40 Saving report: ]8;id=261985;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=897456;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=590878;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\(]8;;\]8;id=630482;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=590878;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\)]8;;\]8;id=261985;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/]8;;\]8;id=897456;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-40/eeg/sub-40_task-SocialMemoryCuing_report.html\sub-40_task-SocialMemoryCuing_report.html]8;;\
│22:54:20│ ⏳️ sub-41 Input:  sub-41_task-SocialMemoryCuing_proc-ica_epo.fif
│22:54:20│ ⏳️ sub-41 Output: sub-41_task-SocialMemoryCuing_proc-clean_epo.fif
│22:54:20│ ⏳️ sub-41 Generating rejection thresholds using autoreject …
│22:54:22│ ⏳️ sub-41 Using PTP rejection thresholds: {'eeg': 0.00020818714120282713}
│22:54:23│ ⏳️ sub-41 Adding cleaned epochs to report.
│22:54:24│ ⏳️ sub-41 Adding config and sys info to report
│22:54:24│ ⏳️ sub-41 Saving report: ]8;id=711178;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=240356;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=615339;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\(]8;;\]8;id=234284;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=615339;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\)]8;;\]8;id=711178;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/]8;;\]8;id=240356;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-41/eeg/sub-41_task-SocialMemoryCuing_report.html\sub-41_task-SocialMemoryCuing_report.html]8;;\
│22:54:24│ ⏳️ sub-43 Input:  sub-43_task-SocialMemoryCuing_proc-ica_epo.fif
│22:54:24│ ⏳️ sub-43 Output: sub-43_task-SocialMemoryCuing_proc-clean_epo.fif
│22:54:24│ ⏳️ sub-43 Generating rejection thresholds using autoreject …
│22:54:26│ ⏳️ sub-43 Using PTP rejection thresholds: {'eeg': 0.0003625088271100986}
│22:54:26│ ⏳️ sub-43 Adding cleaned epochs to report.
│22:54:28│ ⏳️ sub-43 Adding config and sys info to report
│22:54:28│ ⏳️ sub-43 Saving report: ]8;id=79263;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=918425;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=761760;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\(]8;;\]8;id=530908;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=761760;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\)]8;;\]8;id=79263;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/]8;;\]8;id=918425;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-43/eeg/sub-43_task-SocialMemoryCuing_report.html\sub-43_task-SocialMemoryCuing_report.html]8;;\
│22:54:28│ ⏳️ sub-44 Input:  sub-44_task-SocialMemoryCuing_proc-ica_epo.fif
│22:54:28│ ⏳️ sub-44 Output: sub-44_task-SocialMemoryCuing_proc-clean_epo.fif
│22:54:28│ ⏳️ sub-44 Generating rejection thresholds using autoreject …
│22:54:31│ ⏳️ sub-44 Using PTP rejection thresholds: {'eeg': 0.00012111668996930177}
│22:54:31│ ⏳️ sub-44 Adding cleaned epochs to report.
│22:54:32│ ⏳️ sub-44 Adding config and sys info to report
│22:54:32│ ⏳️ sub-44 Saving report: ]8;id=473084;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=252152;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=305728;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\(]8;;\]8;id=893886;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=305728;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\)]8;;\]8;id=473084;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/]8;;\]8;id=252152;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-44/eeg/sub-44_task-SocialMemoryCuing_report.html\sub-44_task-SocialMemoryCuing_report.html]8;;\
│22:54:32│ ⏳️ sub-45 Input:  sub-45_task-SocialMemoryCuing_proc-ica_epo.fif
│22:54:32│ ⏳️ sub-45 Output: sub-45_task-SocialMemoryCuing_proc-clean_epo.fif
│22:54:33│ ⏳️ sub-45 Generating rejection thresholds using autoreject …
│22:54:34│ ⏳️ sub-45 Using PTP rejection thresholds: {'eeg': 0.00011760858671365924}
│22:54:35│ ⏳️ sub-45 Adding cleaned epochs to report.
│22:54:36│ ⏳️ sub-45 Adding config and sys info to report
│22:54:36│ ⏳️ sub-45 Saving report: ]8;id=151351;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=333806;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=554234;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\(]8;;\]8;id=445567;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=554234;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\)]8;;\]8;id=151351;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/]8;;\]8;id=333806;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-45/eeg/sub-45_task-SocialMemoryCuing_report.html\sub-45_task-SocialMemoryCuing_report.html]8;;\
│22:54:36│ ⏳️ sub-46 Input:  sub-46_task-SocialMemoryCuing_proc-ica_epo.fif
│22:54:36│ ⏳️ sub-46 Output: sub-46_task-SocialMemoryCuing_proc-clean_epo.fif
│22:54:36│ ⏳️ sub-46 Generating rejection thresholds using autoreject …
│22:54:39│ ⏳️ sub-46 Using PTP rejection thresholds: {'eeg': 0.00015982971193667916}
│22:54:39│ ⏳️ sub-46 Adding cleaned epochs to report.
│22:54:40│ ⏳️ sub-46 Adding config and sys info to report
│22:54:40│ ⏳️ sub-46 Saving report: ]8;id=146205;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=325736;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=373828;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\(]8;;\]8;id=250297;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=373828;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\)]8;;\]8;id=146205;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/]8;;\]8;id=325736;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-46/eeg/sub-46_task-SocialMemoryCuing_report.html\sub-46_task-SocialMemoryCuing_report.html]8;;\
│22:54:41│ ⏳️ sub-48 Input:  sub-48_task-SocialMemoryCuing_proc-ica_epo.fif
│22:54:41│ ⏳️ sub-48 Output: sub-48_task-SocialMemoryCuing_proc-clean_epo.fif
│22:54:41│ ⏳️ sub-48 Generating rejection thresholds using autoreject …
│22:54:43│ ⏳️ sub-48 Using PTP rejection thresholds: {'eeg': 0.0001405528166801513}
│22:54:43│ ⏳️ sub-48 Adding cleaned epochs to report.
│22:54:45│ ⏳️ sub-48 Adding config and sys info to report
│22:54:45│ ⏳️ sub-48 Saving report: ]8;id=526958;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=37581;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=464328;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\(]8;;\]8;id=496135;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=464328;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\)]8;;\]8;id=526958;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/]8;;\]8;id=37581;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-48/eeg/sub-48_task-SocialMemoryCuing_report.html\sub-48_task-SocialMemoryCuing_report.html]8;;\
│22:54:45│ ⏳️ sub-49 Input:  sub-49_task-SocialMemoryCuing_proc-ica_epo.fif
│22:54:45│ ⏳️ sub-49 Output: sub-49_task-SocialMemoryCuing_proc-clean_epo.fif
│22:54:45│ ⏳️ sub-49 Generating rejection thresholds using autoreject …
│22:54:47│ ⏳️ sub-49 Using PTP rejection thresholds: {'eeg': 0.00010785204602977875}
│22:54:47│ ⏳️ sub-49 Adding cleaned epochs to report.
│22:54:49│ ⏳️ sub-49 Adding config and sys info to report
│22:54:49│ ⏳️ sub-49 Saving report: ]8;id=169;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=700132;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=511661;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\(]8;;\]8;id=53184;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=511661;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\)]8;;\]8;id=169;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/]8;;\]8;id=700132;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-49/eeg/sub-49_task-SocialMemoryCuing_report.html\sub-49_task-SocialMemoryCuing_report.html]8;;\
│22:54:49│ ⏳️ sub-50 Input:  sub-50_task-SocialMemoryCuing_proc-ica_epo.fif
│22:54:49│ ⏳️ sub-50 Output: sub-50_task-SocialMemoryCuing_proc-clean_epo.fif
│22:54:49│ ⏳️ sub-50 Generating rejection thresholds using autoreject …
│22:54:51│ ⏳️ sub-50 Using PTP rejection thresholds: {'eeg': 8.502788811486854e-05}
│22:54:51│ ⏳️ sub-50 Adding cleaned epochs to report.
│22:54:53│ ⏳️ sub-50 Adding config and sys info to report
│22:54:53│ ⏳️ sub-50 Saving report: ]8;id=147521;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\/home/fspletti/vorlesungen/]8;;\]8;id=835985;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\2023S_Signal_processing_and_Analysis_of_human_brain_potentials_]8;;\]8;id=32895;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\(]8;;\]8;id=758540;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\EEG]8;;\]8;id=32895;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\)]8;;\]8;id=147521;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/]8;;\]8;id=835985;file:///home/fspletti/vorlesungen/2023S_Signal_processing_and_Analysis_of_human_brain_potentials_(EEG)/git/tmp/eeg_course_project_beta/data/ds003702/derivatives/mne-bids-pipeline/sub-50/eeg/sub-50_task-SocialMemoryCuing_report.html\sub-50_task-SocialMemoryCuing_report.html]8;;\
└────────┴ done (2m 51s)
In [73]:
# checkup: plot original (conventionally filtered) epochs
curr_checkup_epochs = mne.read_epochs(f"{curr_subject_path}/sub-01_task-SocialMemoryCuing_epo.fif")
mne.viz.plot_epochs_image(curr_checkup_epochs)
print("checkup: original epochs")
No description has been provided for this image 
checkup: original epochs
In [74]:
# checkup: plot cleaned epochs
curr_checkup_epochs_ptp = mne.read_epochs(f"{curr_subject_path}/sub-01_task-SocialMemoryCuing_proc-clean_epo.fif")
mne.viz.plot_epochs_image(curr_checkup_epochs_ptp)
print("checkup: original (top) vs. cleaned epochs (bottom)")
No description has been provided for this image 
checkup: original (top) vs. cleaned epochs (bottom)

In this checkup plot, the again reduced peak amplitudes and lowered number of epochs are visible in contrast to the original and ICA-output plots. Both are expected when applying the PTP.

In this plot, increased absolute values in similar time frames are visible over many or most of the epochs. These time frames of increased absolute amplitudes seem to match the ones of the average amplitude.

Analysis¶

The pre-processing steps get followed by the analysis steps.

Analysis: Sensor¶

Some plots including topography plot and power per electrode position/epoch/time are given by the separate notebook more_visuals.ipynb.

The topography plot indicates high amplitudes located in the front of the head. For other regions, the absolute value of the energy seems to be lower.

In the power over time plot per electrode, increased power is visible for several time frames. This is visible through the little or missing change over multiple epochs.

In [46]:
curr_steps = "sensor"
if curr_steps in STEPS_TO_RUN and STEPS_TO_RUN[curr_steps]:
    !mne_bids_pipeline --config {config_path} --steps {curr_steps}

┌────────┬ Welcome aboard MNE-BIDS-Pipeline! 👋 ────────────────────────────────
│23:55:37│ 📝 Using configuration: ./mne-bids/config/mne-bids-pipeline.py
└────────┴ 
┌────────┬ init/_01_init_derivatives_dir ───────────────────────────────────────
│23:55:37│ ✅ Output directories already exist …
└────────┴ done (1s)
┌────────┬ init/_02_find_empty_room ────────────────────────────────────────────
│23:55:37│ ⏩ Skipping, empty-room data only relevant for MEG …
└────────┴ done (1s)
┌────────┬ sensor/_01_make_evoked ──────────────────────────────────────────────
│23:55:38│ ✅ sub-01 Computation unnecessary (cached) …
│23:55:38│ ✅ sub-02 Computation unnecessary (cached) …
│23:55:38│ ✅ sub-04 Computation unnecessary (cached) …
│23:55:38│ ✅ sub-07 Computation unnecessary (cached) …
│23:55:38│ ✅ sub-09 Computation unnecessary (cached) …
│23:55:38│ ✅ sub-10 Computation unnecessary (cached) …
│23:55:38│ ✅ sub-11 Computation unnecessary (cached) …
│23:55:38│ ✅ sub-12 Computation unnecessary (cached) …
│23:55:38│ ✅ sub-13 Computation unnecessary (cached) …
│23:55:38│ ✅ sub-14 Computation unnecessary (cached) …
│23:55:38│ ✅ sub-16 Computation unnecessary (cached) …
│23:55:38│ ✅ sub-15 Computation unnecessary (cached) …
│23:55:38│ ✅ sub-17 Computation unnecessary (cached) …
│23:55:38│ ✅ sub-18 Computation unnecessary (cached) …
│23:55:38│ ✅ sub-19 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-21 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-22 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-24 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-23 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-26 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-25 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-27 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-30 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-28 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-33 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-32 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-34 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-38 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-35 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-40 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-39 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-41 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-44 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-43 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-46 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-45 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-48 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-49 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-50 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-03 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-06 Computation unnecessary (cached) …
└────────┴ done (2s)
┌────────┬ sensor/_02_decoding_full_epochs ─────────────────────────────────────
│23:55:39│ ✅ sub-04 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-02 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-07 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-06 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-03 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-01 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-10 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-09 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-11 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-12 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-15 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-14 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-13 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-17 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-19 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-22 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-16 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-18 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-23 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-21 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-28 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-24 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-26 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-32 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-34 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-38 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-30 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-35 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-33 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-25 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-27 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-39 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-40 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-45 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-43 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-46 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-41 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-48 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-49 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-50 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-44 Computation unnecessary (cached) …
└────────┴ done (1s)
┌────────┬ sensor/_03_decoding_time_by_time ────────────────────────────────────
│23:55:39│ ✅ sub-01 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-02 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-03 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-04 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-06 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-07 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-09 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-10 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-11 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-12 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-13 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-14 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-15 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-16 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-17 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-18 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-19 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-21 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-22 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-23 Computation unnecessary (cached) …
│23:55:39│ ✅ sub-24 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-25 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-26 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-27 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-28 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-30 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-32 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-33 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-34 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-35 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-38 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-39 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-40 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-41 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-43 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-44 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-45 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-46 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-48 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-49 Computation unnecessary (cached) …
│23:55:40│ ✅ sub-50 Computation unnecessary (cached) …
└────────┴ done (1s)
┌────────┬ sensor/_04_time_frequency ───────────────────────────────────────────
│23:55:40│ ⏳️ sub-01 Reading sub-01_task-SocialMemoryCuing_proc-clean_epo.fif
│23:55:40│ ⏳️ sub-01 Computing TFR for avatar
│23:55:42│ ⏳️ sub-01 Computing TFR for sticks
│23:55:43│ ⏳️ sub-01 Computing TFR for Congruence=='Incongruent'
│23:55:43│ 🔂 sub-01 A critical error occurred. The error message was: 'Event name "Congruence==\'Incongruent\'" could not be found. The following events are present in the data: avatar, sticks The epochs.metadata Pandas query did not yield any results: name \'Congruence\' is not defined'

Continuing pipeline run.
│23:55:43│ ⏳️ sub-02 Reading sub-02_task-SocialMemoryCuing_proc-clean_epo.fif
│23:55:43│ ⏳️ sub-02 Computing TFR for avatar
│23:55:44│ ⏳️ sub-02 Computing TFR for sticks
│23:55:45│ ⏳️ sub-02 Computing TFR for Congruence=='Incongruent'
│23:55:45│ 🔂 sub-02 A critical error occurred. The error message was: 'Event name "Congruence==\'Incongruent\'" could not be found. The following events are present in the data: avatar, sticks The epochs.metadata Pandas query did not yield any results: name \'Congruence\' is not defined'

Continuing pipeline run.
│23:55:45│ ✅ sub-03 Computation unnecessary (cached) …
│23:55:45│ ✅ sub-04 Computation unnecessary (cached) …
│23:55:45│ ✅ sub-06 Computation unnecessary (cached) …
│23:55:45│ ⏳️ sub-07 Reading sub-07_task-SocialMemoryCuing_proc-clean_epo.fif
│23:55:45│ ⏳️ sub-07 Computing TFR for avatar
│23:55:45│ ⏳️ sub-07 Computing TFR for sticks
│23:55:46│ ⏳️ sub-07 Computing TFR for Congruence=='Incongruent'
│23:55:46│ 🔂 sub-07 A critical error occurred. The error message was: 'Event name "Congruence==\'Incongruent\'" could not be found. The following events are present in the data: avatar, sticks The epochs.metadata Pandas query did not yield any results: name \'Congruence\' is not defined'

Continuing pipeline run.
│23:55:46│ ✅ sub-09 Computation unnecessary (cached) …
│23:55:46│ ⏳️ sub-10 Reading sub-10_task-SocialMemoryCuing_proc-clean_epo.fif
│23:55:46│ ⏳️ sub-10 Computing TFR for avatar
│23:55:47│ ⏳️ sub-10 Computing TFR for sticks
│23:55:48│ ⏳️ sub-10 Computing TFR for Congruence=='Incongruent'
│23:55:48│ 🔂 sub-10 A critical error occurred. The error message was: 'Event name "Congruence==\'Incongruent\'" could not be found. The following events are present in the data: avatar, sticks The epochs.metadata Pandas query did not yield any results: name \'Congruence\' is not defined'

Continuing pipeline run.
│23:55:48│ ✅ sub-11 Computation unnecessary (cached) …
│23:55:48│ ✅ sub-12 Computation unnecessary (cached) …
│23:55:48│ ⏳️ sub-13 Reading sub-13_task-SocialMemoryCuing_proc-clean_epo.fif
│23:55:48│ ⏳️ sub-13 Computing TFR for avatar
│23:55:49│ ⏳️ sub-13 Computing TFR for sticks
│23:55:50│ ⏳️ sub-13 Computing TFR for Congruence=='Incongruent'
│23:55:50│ 🔂 sub-13 A critical error occurred. The error message was: 'Event name "Congruence==\'Incongruent\'" could not be found. The following events are present in the data: avatar, sticks The epochs.metadata Pandas query did not yield any results: name \'Congruence\' is not defined'

Continuing pipeline run.
│23:55:50│ ✅ sub-14 Computation unnecessary (cached) …
│23:55:50│ ✅ sub-15 Computation unnecessary (cached) …
│23:55:50│ ✅ sub-16 Computation unnecessary (cached) …
│23:55:50│ ✅ sub-17 Computation unnecessary (cached) …
│23:55:50│ ✅ sub-18 Computation unnecessary (cached) …
│23:55:50│ ✅ sub-19 Computation unnecessary (cached) …
│23:55:50│ ✅ sub-21 Computation unnecessary (cached) …
│23:55:50│ ✅ sub-22 Computation unnecessary (cached) …
│23:55:50│ ✅ sub-23 Computation unnecessary (cached) …
│23:55:50│ ⏳️ sub-24 Reading sub-24_task-SocialMemoryCuing_proc-clean_epo.fif
│23:55:51│ ⏳️ sub-24 Computing TFR for avatar
│23:55:51│ ⏳️ sub-24 Computing TFR for sticks
│23:55:52│ ⏳️ sub-24 Computing TFR for Congruence=='Incongruent'
│23:55:52│ 🔂 sub-24 A critical error occurred. The error message was: 'Event name "Congruence==\'Incongruent\'" could not be found. The following events are present in the data: avatar, sticks The epochs.metadata Pandas query did not yield any results: name \'Congruence\' is not defined'

Continuing pipeline run.
│23:55:52│ ✅ sub-25 Computation unnecessary (cached) …
│23:55:52│ ⏳️ sub-26 Reading sub-26_task-SocialMemoryCuing_proc-clean_epo.fif
│23:55:52│ ⏳️ sub-26 Computing TFR for avatar
│23:55:53│ ⏳️ sub-26 Computing TFR for sticks
│23:55:54│ ⏳️ sub-26 Computing TFR for Congruence=='Incongruent'
│23:55:54│ 🔂 sub-26 A critical error occurred. The error message was: 'Event name "Congruence==\'Incongruent\'" could not be found. The following events are present in the data: avatar, sticks The epochs.metadata Pandas query did not yield any results: name \'Congruence\' is not defined'

Continuing pipeline run.
│23:55:54│ ✅ sub-27 Computation unnecessary (cached) …
│23:55:54│ ✅ sub-28 Computation unnecessary (cached) …
│23:55:54│ ✅ sub-30 Computation unnecessary (cached) …
│23:55:54│ ✅ sub-32 Computation unnecessary (cached) …
│23:55:54│ ✅ sub-33 Computation unnecessary (cached) …
│23:55:54│ ⏳️ sub-34 Reading sub-34_task-SocialMemoryCuing_proc-clean_epo.fif
│23:55:54│ ⏳️ sub-34 Computing TFR for avatar
│23:55:55│ ⏳️ sub-34 Computing TFR for sticks
│23:55:56│ ⏳️ sub-34 Computing TFR for Congruence=='Incongruent'
│23:55:56│ 🔂 sub-34 A critical error occurred. The error message was: 'Event name "Congruence==\'Incongruent\'" could not be found. The following events are present in the data: avatar, sticks The epochs.metadata Pandas query did not yield any results: name \'Congruence\' is not defined'

Continuing pipeline run.
│23:55:56│ ✅ sub-35 Computation unnecessary (cached) …
│23:55:56│ ✅ sub-38 Computation unnecessary (cached) …
│23:55:56│ ✅ sub-39 Computation unnecessary (cached) …
│23:55:56│ ⏳️ sub-40 Reading sub-40_task-SocialMemoryCuing_proc-clean_epo.fif
│23:55:56│ ⏳️ sub-40 Computing TFR for avatar
│23:55:57│ ⏳️ sub-40 Computing TFR for sticks
│23:55:58│ ⏳️ sub-40 Computing TFR for Congruence=='Incongruent'
│23:55:58│ 🔂 sub-40 A critical error occurred. The error message was: 'Event name "Congruence==\'Incongruent\'" could not be found. The following events are present in the data: avatar, sticks The epochs.metadata Pandas query did not yield any results: name \'Congruence\' is not defined'

Continuing pipeline run.
│23:55:58│ ✅ sub-41 Computation unnecessary (cached) …
│23:55:58│ ✅ sub-43 Computation unnecessary (cached) …
│23:55:58│ ✅ sub-44 Computation unnecessary (cached) …
│23:55:58│ ⏳️ sub-45 Reading sub-45_task-SocialMemoryCuing_proc-clean_epo.fif
│23:55:58│ ⏳️ sub-45 Computing TFR for avatar
│23:55:59│ ⏳️ sub-45 Computing TFR for sticks
│23:56:00│ ⏳️ sub-45 Computing TFR for Congruence=='Incongruent'
│23:56:00│ 🔂 sub-45 A critical error occurred. The error message was: 'Event name "Congruence==\'Incongruent\'" could not be found. The following events are present in the data: avatar, sticks The epochs.metadata Pandas query did not yield any results: name \'Congruence\' is not defined'

Continuing pipeline run.
│23:56:00│ ⏳️ sub-46 Reading sub-46_task-SocialMemoryCuing_proc-clean_epo.fif
│23:56:00│ ⏳️ sub-46 Computing TFR for avatar
│23:56:01│ ⏳️ sub-46 Computing TFR for sticks
│23:56:02│ ⏳️ sub-46 Computing TFR for Congruence=='Incongruent'
│23:56:02│ 🔂 sub-46 A critical error occurred. The error message was: 'Event name "Congruence==\'Incongruent\'" could not be found. The following events are present in the data: avatar, sticks The epochs.metadata Pandas query did not yield any results: name \'Congruence\' is not defined'

Continuing pipeline run.
│23:56:02│ ✅ sub-48 Computation unnecessary (cached) …
│23:56:02│ ✅ sub-49 Computation unnecessary (cached) …
│23:56:02│ ⏳️ sub-50 Reading sub-50_task-SocialMemoryCuing_proc-clean_epo.fif
│23:56:02│ ⏳️ sub-50 Computing TFR for avatar
│23:56:03│ ⏳️ sub-50 Computing TFR for sticks
│23:56:03│ ⏳️ sub-50 Computing TFR for Congruence=='Incongruent'
│23:56:03│ 🔂 sub-50 A critical error occurred. The error message was: 'Event name "Congruence==\'Incongruent\'" could not be found. The following events are present in the data: avatar, sticks The epochs.metadata Pandas query did not yield any results: name \'Congruence\' is not defined'

Continuing pipeline run.
└────────┴ done (24s)
┌────────┬ sensor/_05_decoding_csp ─────────────────────────────────────────────
│23:56:05│ ✅ sub-01 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-02 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-06 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-04 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-09 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-03 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-10 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-11 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-12 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-13 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-14 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-15 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-16 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-17 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-18 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-19 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-21 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-22 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-23 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-24 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-25 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-26 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-28 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-27 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-30 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-32 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-33 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-34 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-35 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-38 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-39 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-40 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-41 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-07 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-43 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-44 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-45 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-46 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-48 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-49 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-50 Computation unnecessary (cached) …
└────────┴ done (2s)
┌────────┬ sensor/_06_make_cov ─────────────────────────────────────────────────
│23:56:05│ ✅ sub-04 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-01 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-07 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-02 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-03 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-06 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-09 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-10 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-13 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-15 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-17 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-12 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-11 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-14 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-19 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-16 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-18 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-21 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-24 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-22 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-28 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-26 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-32 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-34 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-30 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-33 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-25 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-23 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-35 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-27 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-38 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-40 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-43 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-46 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-48 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-39 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-45 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-41 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-44 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-50 Computation unnecessary (cached) …
│23:56:05│ ✅ sub-49 Computation unnecessary (cached) …
└────────┴ done (1s)
┌────────┬ sensor/_99_group_average ────────────────────────────────────────────
│23:56:06│ ✅ sub-average Computation unnecessary (cached) …
│23:56:06│ ✅ sub-average Computation unnecessary (cached) …
│23:56:06│ ✅ sub-average Computation unnecessary (cached) …
│23:56:06│ ✅ sub-average Computation unnecessary (cached) …
│23:56:06│ ✅ sub-average Computation unnecessary (cached) …
└────────┴ done (1s)

In the sensor/_04_time_frequency step, the error message regarding missing events for subjects 1, 2, 7, 10, 13, 24, 26, 34, 40, 45, 46, and 50 is expected. Here, the given data set seems to be incomplete.

Another short test is printing the average Receiver Operating Characteristic Area Under the Curve (ROC AUC) results file content. This checkup returns headings and values.

Since the content gets printed, the matching file for average ROC AUC output is known to exist.

In [47]:
cmd.cat("./data/ds003702/derivatives/mne-bids-pipeline/sub-01/eeg/sub-01_task-SocialMemoryCuing_proc-avatar+sticks+FullEpochs+rocauc_decoding.tsv")

cond_1	cond_2	mean_crossval_score	metric

avatar	sticks	0.8913935574229692	roc_auc

In order to also include the validity of the cue, we modified the time-frequency conditions for the pipeline to also include groups seperated by their validity. Due to MNE-Bids apparently not supporting manual labeling of epochs, we also included the queries needed to get all permutations of valid and invalid cues. This results in somewhat funny looking labels in the final report, but has no apparent drawbacks otherwise.

Analysis: Source Space Analysis¶

In [48]:
curr_steps = "source"
if curr_steps in STEPS_TO_RUN and STEPS_TO_RUN[curr_steps]:
    !mne_bids_pipeline --config {config_path} --steps {curr_steps}

┌────────┬ Welcome aboard MNE-BIDS-Pipeline! 👋 ────────────────────────────────
│23:59:36│ 📝 Using configuration: ./mne-bids/config/mne-bids-pipeline.py
└────────┴ 
┌────────┬ init/_01_init_derivatives_dir ───────────────────────────────────────
│23:59:36│ ✅ Output directories already exist …
└────────┴ done (1s)
┌────────┬ init/_02_find_empty_room ────────────────────────────────────────────
│23:59:36│ ⏩ Skipping, empty-room data only relevant for MEG …
└────────┴ done (1s)
┌────────┬ source/_01_make_bem_surfaces ────────────────────────────────────────
│23:59:36│ ⏩ Skipping, BEM surface extraction not needed for MRI template …
└────────┴ done (1s)
┌────────┬ source/_02_make_bem_solution ────────────────────────────────────────
│23:59:36│ ⏩ Skipping, BEM solution computation not needed for MRI template …
└────────┴ done (1s)
┌────────┬ source/_03_setup_source_space ───────────────────────────────────────
│23:59:37│ ✅ sub-fsaverage Computation unnecessary (cached) …
└────────┴ done (2s)
┌────────┬ source/_04_make_forward ─────────────────────────────────────────────
│23:59:37│ ✅ sub-07 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-09 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-10 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-11 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-12 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-13 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-14 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-15 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-16 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-17 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-18 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-19 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-21 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-22 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-23 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-24 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-25 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-26 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-27 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-28 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-30 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-32 Computation unnecessary (cached) …
│23:59:37│ ✅ sub-33 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-34 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-35 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-38 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-39 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-40 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-41 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-43 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-44 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-45 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-46 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-48 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-49 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-50 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-01 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-03 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-06 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-04 Computation unnecessary (cached) …
│23:59:38│ ✅ sub-02 Computation unnecessary (cached) …
└────────┴ done (2s)
┌────────┬ source/_05_make_inverse ─────────────────────────────────────────────
│23:59:39│ ✅ sub-02 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-01 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-07 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-04 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-03 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-06 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-10 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-09 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-11 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-12 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-13 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-15 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-17 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-22 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-19 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-14 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-24 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-16 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-18 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-21 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-23 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-25 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-26 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-28 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-34 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-38 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-32 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-40 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-30 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-35 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-39 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-27 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-33 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-41 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-43 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-45 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-46 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-48 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-50 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-44 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-49 Computation unnecessary (cached) …
└────────┴ done (1s)
┌────────┬ source/_99_group_average ────────────────────────────────────────────
│23:59:39│ ✅ sub-02 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-04 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-03 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-07 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-01 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-06 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-10 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-11 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-09 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-15 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-19 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-13 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-17 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-12 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-14 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-21 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-16 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-18 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-24 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-26 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-22 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-28 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-32 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-34 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-33 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-30 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-25 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-27 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-35 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-23 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-38 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-40 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-46 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-45 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-43 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-39 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-48 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-41 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-49 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-50 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-44 Computation unnecessary (cached) …
│23:59:39│ ✅ sub-average Computation unnecessary (cached) …
└────────┴ done (1s)

In order to view all of the results of this step and the previous ones, please view the full reports generated by the MNE BIDS pipeline.

Files per Step¶

To allow for additional investigation on the processed signals, the following list contains the exported files per step for the first subject. These file names shall also help to interprete the check ups performed by printing file names of existing files.

The ? symbols are single letter placeholders, which also work with terminal commands like ls to e. g. display all subjects files. They need to get replaced by the subject index as 2 digit string. This is an example: ?? → 01

  • general results files

    ./data/ds003702/derivatives/mne-bids-pipeline/sub-??/eeg/sub-??_task-SocialMemoryCuing_proc-ica+components_report.html
./data/ds003702/derivatives/mne-bids-pipeline/sub-??/eeg/sub-??_task-SocialMemoryCuing_proc-ica_report.html
./data/ds003702/derivatives/mne-bids-pipeline/sub-??/eeg/sub-??_task-SocialMemoryCuing_report.html
./data/ds003702/derivatives/mne-bids-pipeline/sub-average/eeg/sub-average_task-SocialMemoryCuing_report.html

  • preprocessing/_01_data_quality

    sub-??_task-SocialMemoryCuing_report.h5
sub-??_task-SocialMemoryCuing_report.h5.lock
sub-??_task-SocialMemoryCuing_report.html

  • preprocessing/_04_frequency_filter

    sub-??_task-SocialMemoryCuing_proc-filt_raw.fif

  • preprocessing/_05_make_epochs

    sub-??_task-SocialMemoryCuing_epo.fif

  • preprocessing/_06a_run_ica

    sub-??_task-SocialMemoryCuing_ica.fif
sub-??_task-SocialMemoryCuing_proc-ica_components.tsv
sub-??_task-SocialMemoryCuing_proc-ica+components_report.html

  • ica labelling: no new file (just changes of *.tsv file)

  • preprocessing/_07a_apply_ica

    sub-??_task-SocialMemoryCuing_proc-ica_epo.fif
sub-??_task-SocialMemoryCuing_proc-ica_report.html

  • preprocessing/_08_ptp_reject

    sub-??_task-SocialMemoryCuing_proc-clean_epo.fif

  • sensor

    sub-??_task-SocialMemoryCuing_ave.fif  # average data

# decoding analysis results related to ROC AUC (Receiver Operating Characteristic Area Under the Curve) metric, Matlab and tab separated file versions:
sub-??_task-SocialMemoryCuing_proc-avatar+sticks+FullEpochs+rocauc_decoding.mat
sub-??_task-SocialMemoryCuing_proc-avatar+sticks+FullEpochs+rocauc_decoding.tsv
sub-??_task-SocialMemoryCuing_proc-avatar+sticks+TimeByTime+rocauc_decoding.mat
sub-??_task-SocialMemoryCuing_proc-avatar+sticks+TimeByTime+rocauc_decoding.tsv

# time frequency analysis results related to Time-Frequency Representation (TFR):
sub-??_task-SocialMemoryCuing_itc+avatar+tfr.h5   # Inter-Trial Coherence (ITC)
sub-??_task-SocialMemoryCuing_itc+sticks+tfr.h5
sub-??_task-SocialMemoryCuing_power+avatar+tfr.h5 # power spectral density (PSD) 
sub-??_task-SocialMemoryCuing_power+sticks+tfr.h5

sub-??_task-SocialMemoryCuing_cov.fif
sub-??_task-SocialMemoryCuing_proc-avatar+sticks+CSP+rocauc_decoding.xlsx

  • source

    sub-??_task-SocialMemoryCuing_fwd.fif
sub-??_task-SocialMemoryCuing_trans.fif

Further Comparison¶

As a final check-up, the power spectra for each subjects alpha and theta waves get plotted for two time ranges, each.

In [49]:
SUBJECT_IDS = [ "01", "02", "03", "04",       "06", "07",       "09", "10",
                "11", "12", "13", "14", "15", "16", "17", "18", "19",      
                "21", "22", "23", "24", "25", "26", "27", "28",       "30",
                      "32", "33", "34", "35",             "38", "39", "40",
                "41",       "43", "44", "45", "46",       "48", "49", "50"]

data_path = cfg.bids_root
cues_list = ['avatar', 'sticks']
bands_list = ['alpha', 'theta']
time_ranges = [[2, 3], [3.6, 4]]
# '{data}/derivatives/mne-bids-pipeline/sub-{sub}/eeg/sub-{sub}_task-SocialMemoryCuing_power+{cue}+tfr.h5'
In [50]:
from IPython.core.display import Markdown
from IPython.display import display, display_markdown

for subject_str in SUBJECT_IDS:
    display_markdown(Markdown("## Subject: {}".format(subject_str)))
    for idx_cue in range(len(cues_list)):
        for idx_time in range(len(time_ranges)):
            fig, axes = plt.subplots(1, 2)
    
            curr_filename_str = f"plot_power_sub-{subject_str}_{cues_list[idx_cue]}_" + \
                                f"{time_ranges[idx_time][0]:01.1f}-{time_ranges[idx_time][1]:01.1f}.png"
            
            for idx_band in range(len(bands_list)):
                
                #print(curr_filename_str)
                pwr = pp.plot_power(
                    config_path = config_path,
                    subject = subject_str,
                    cue = cues_list[idx_cue],
                    band = bands_list[idx_band],
                    time_range = time_ranges[idx_time],
                )
                fig_power = pwr.plot_topomap(ch_type='eeg', show=True, axes=axes[idx_band])
                axes[idx_band].set_title('{}: {} from {} s to {} s'.format(cues_list[idx_cue], bands_list[idx_band], *time_ranges[idx_time]))
            fig.set_size_inches(10, 5)
            fig.savefig(curr_filename_str)
            display(fig)
            plt.close(fig)

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Finally, we attempt to replicate plots from the paper.

In [51]:
# split epochs to valid and invalid ones
from mne import EvokedArray

valid_epochs = []
invalid_epochs = []


FILE_PATH_TEMPLATE = '{data}/derivatives/mne-bids-pipeline/sub-{sub}/eeg/sub-{sub}_task-SocialMemoryCuing_proc-clean_epo.fif'

for sub_str in CLEAN_SUBJECT_IDS:
    path = FILE_PATH_TEMPLATE.format(data=cfg.bids_root, sub=sub_str)
    
    epochs: EpochsFIF = mne.read_epochs(path)
    
    incongruentAvg: EvokedArray = epochs["Congruence=='Incongruent' and event_name=='sticks'"]
    congruentAvg: EvokedArray = epochs["Congruence=='Congruent'"]
        
    valid_epochs.append(congruentAvg)
    invalid_epochs.append(incongruentAvg)
In [52]:
# run t test and print the results
from scipy.stats import ttest_ind

ELECTRODES = ['Fp1', 'Fpz', 'Fp2' , 'F7', 'F3', 'Fz', 'F4', 'F8', 'FC5', 'FC1', 'FC2', 'FC6', 'M1', 'T7', 'C3', 'Cz', 'C4', 'T8', 'M2', 'CP5', 'CP1', 'CP2', 'CP6', 'P7', 'P3', 'Pz', 'P4', 'P8', 'POz', 'O1', 'O2', 'AF7', 'AF3', 'AF4', 'AF8', 'F5', 'F1', 'F2', 'F6', 'FC3', 'FCz', 'FC4', 'C5', 'C1', 'C2', 'C6', 'CP3', 'CP4', 'P5', 'P1', 'P2', 'P6', 'PO5', 'PO3', 'PO4', 'PO6', 'FT7', 'FT8', 'TP7', 'TP8', 'PO7', 'PO8', 'Oz']

TIME = 'time'

def t_test(epochsA, epochsB, time_range=(-1, 4)):
    result = DataFrame()
    
    
    aframe: DataFrame = epochsA.to_data_frame()
    aframe = aframe[(min(time_range) <= aframe[TIME]) & (aframe[TIME] <= max(time_range))]
    bframe: DataFrame = epochsB.to_data_frame()
    bframe = bframe[(min(time_range) <= bframe[TIME]) & (bframe[TIME] <= max(time_range))]
    
    for electrode in ELECTRODES:
        result[electrode] = ttest_ind(aframe[electrode], bframe[electrode])
    
    return result


t_testresult2 = t_test(valid_epochs[0], invalid_epochs[1], time_range=(2.0, 3.0))
display_markdown(Markdown("## T-Test between Valid and Invalid cues, between 2 s and 3 s"))
display(t_testresult2)
    
t_testresult = t_test(valid_epochs[0], invalid_epochs[1], time_range=(3.6, 4.0))
display_markdown(Markdown("## T-Test between Valid and Invalid cues, between 3.6 s and 4 s"))
display(t_testresult)

T-Test between Valid and Invalid cues, between 2 s and 3 s¶

Fp1 Fpz Fp2 F7 F3 Fz F4 F8 FC5 FC1 ... PO3 PO4 PO6 FT7 FT8 TP7 TP8 PO7 PO8 Oz
0 3.178281 -2.327406 -0.33443 -0.123239 5.199024e+00 5.775914e+00 2.681704 5.640409e+00 0.779765 7.545931e+00 ... 1.304566 -9.134319e+00 -0.203935 -3.842111 1.301331 -0.846324 -0.005756 2.067129 -2.099847 0.697671
1 0.001485 0.019957 0.73806 0.901919 2.029968e-07 7.806892e-09 0.007333 1.727414e-08 0.435542 4.751055e-14 ... 0.192061 7.418110e-20 0.838407 0.000122 0.193165 0.397385 0.995407 0.038739 0.035759 0.485394

2 rows × 63 columns

T-Test between Valid and Invalid cues, between 3.6 s and 4 s¶

Fp1 Fpz Fp2 F7 F3 Fz F4 F8 FC5 FC1 ... PO3 PO4 PO6 FT7 FT8 TP7 TP8 PO7 PO8 Oz
0 1.320759e+01 5.339318e+00 1.247452e+01 7.601367e+00 6.780993e+00 6.438220e+00 5.940530e+00 1.547572e+01 6.504385e+00 6.544054e+00 ... -1.192748e+01 -7.101773e+00 -9.787763e+00 4.332294 8.408877e+00 3.239867 -3.451819 -6.348297e+00 -1.261125e+01 -7.585224e+00
1 2.777130e-39 9.671142e-08 2.796616e-35 3.378577e-14 1.307306e-11 1.302139e-10 2.999734e-09 5.243847e-53 8.428845e-11 6.481102e-11 ... 1.968345e-32 1.373634e-12 1.866935e-22 0.000015 5.115313e-17 0.001202 0.000561 2.335893e-10 5.202704e-36 3.822509e-14

2 rows × 63 columns

Finally, we computed the two-sample t-test between valid and invalid cues for each electrode. In order to interpret the tables provided, the top row (with index 0) is the t-statistic and the bottom row (with index 1) is the p-value.

Overall, we think that our results match the results presented by Gregory et al.